AUTOMATICALLY CREATING A MAPPING BETWEEN TEXT DATA AND AUDIO DATA
Techniques are provided for creating a mapping that maps locations in audio data (e.g., an audio book) to corresponding locations in text data (e.g., an e-book). Techniques are provided for using a mapping between audio data and text data, whether or not the mapping is created automatically or manually. A mapping may be used for bookmark switching where a bookmark established in one version of a digital work is used to identify a corresponding location with another version of the digital work. Alternatively, the mapping may be used to play audio that corresponds to text selected by a user. Alternatively, the mapping may be used to automatically highlight text in response to audio that corresponds to the text being played. Alternatively, the mapping may be used to determine where an annotation created in one media context (e.g., audio) will be consumed in another media context (e.g., text).
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The present application claims priority to U.S. Provisional Patent Application No. 61/493,372, entitled “Automatically Creating A Mapping Between Text Data And Audio Data And Switching Between Text Data And Audio Data Based On A Mapping,” filed on Jun. 3, 2011, invented by Alan C. Cannistraro, et al., the entire disclosure of which is incorporated by reference for all purposes as if fully set forth herein.
The present application claims priority to U.S. Provisional Patent Application No. 61/494,375, entitled “Automatically Creating A Mapping Between Text Data And Audio Data And Switching Between Text Data And Audio Data Based On A Mapping,” filed on Jun. 7, 2011, invented by Alan C. Cannistraro, et al., the entire disclosure of which is incorporated by reference for all purposes as if fully set forth herein.
The present application is related to U.S. patent application Ser. No. ______ entitled “Switching Between Text Data and Audio Data Based on a Mapping,” filed on the same day herewith, the entire disclosure of which is incorporated by reference for all purposes as if fully set forth herein.
FIELD OF THE INVENTIONThe present invention relates to automatically creating a mapping between text data and audio data by analyzing the audio data to detect words reflected therein and compare those words to words in the document.
BACKGROUNDWith the cost of handheld electronic devices decreasing and large demand for digital content, creative works that have once been published on printed media are increasingly becoming available as digital media. For example, digital books (also known as “e-books”) are increasingly popular, along with specialized handheld electronic devices known as e-book readers (or “e-readers”). Also, other handheld devices, such as tablet computers and smart phones, although not designed solely as e-readers, have the capability to be operated as e-readers.
A common standard by which e-books are formatted is the EPUB standard (short for “electronic publication”), which is a free and open e-book standard by the International Digital Publishing Forum (IDPF). An EPUB file uses XHTML 1.1 (or DTBook) to construct the content of a book. Styling and layout are performed using a subset of CSS, referred to as OPS Style Sheets.
For some written works, especially those that become popular, an audio version of the written work is created. For example, a recording of a famous individual (or one with a pleasant voice) reading a written work is created and made available for purchase, whether online or in a brick and mortar store.
It is not uncommon for consumers to purchase both an e-book and an audio version (or “audio book”) of the e-book. In some cases, a user reads the entirety of an e-book and then desires to listen to the audio book. In other cases, a user transitions between reading and listening to the book, based on the user's circumstances. For example, while engaging in sports or driving during a commute, the user will tend to listen to the audio version of the book. On the other hand, when lounging in a sofa-chair prior to bed, the user will tend to read the e-book version of the book. Unfortunately, such transitions can be painful, since the user must remember where she stopped in the e-book and manually locate where to begin in the audio book, or visa-versa. Even if the user remembers clearly what was happening in the book where the user left off, such transitions can still be painful because knowing what is happening does not necessarily make it easy to find the portion of an eBook or audio book that corresponds to those happenings. Thus, switching between an e-book and an audio book may be extremely time-consuming.
The specification “EPUB Media Overlays 3.0” defines a usage of SMIL (Synchronized Multimedia Integration Language), the Package Document, the EPUB Style Sheet, and the EPUB Content Document for representation of synchronized text and audio publications. A pre-recorded narration of a publication can be represented as a series of audio clips, each corresponding to part of the text. Each single audio clip, in the series of audio clips that make up a pre-recorded narration, typically represents a single phrase or paragraph, but infers no order relative to the other clips or to the text of a document. Media Overlays solve this problem of synchronization by tying the structured audio narration to its corresponding text in the EPUB Content Document using SMIL markup. Media Overlays are a simplified subset of SMIL 3.0 that allow the playback sequence of these clips to be defined.
Unfortunately, creating Media Overlay files is largely a manual process. Consequently, the granularity of the mapping between audio and textual versions of a work is very coarse. For example, a media overlay file may associate the beginning of each paragraph in an e-book with a corresponding location in an audio version of the book. The reason that media overlay files, especially for novels, do not contain a mapping at any finer level of granularity, such as on a word-by-word basis, is that creating such a highly granular media overlay file might take countless hours in human labor.
The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.
In the drawings:
In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the present invention. It will be apparent, however, that the present invention may be practiced without these specific details. In other instances, well-known structures and devices are shown in block diagram form in order to avoid unnecessarily obscuring the present invention.
Overview of Automatic Generation of Audio-to-Text MappingAccording to one approach, a mapping is automatically created where the mapping maps locations within an audio version of a work (e.g., an audio book) with corresponding locations in a textual version of the work (e.g., an e-book). The mapping is created by performing a speech-to-text analysis on the audio version to identify words reflected in the audio version. The identified words are matched up with the corresponding words in the textual version of the work. The mapping associates locations (within the audio version) of the identified words with locations in the textual version of the work where the identified words are found.
Audio Version FormatsThe audio data reflects an audible reading of text of a textual version of a work, such as a book, web page, pamphlet, flyer, etc. The audio data may be stored in one or more audio files. The one or more audio files may be in one of many file formats. Non-limiting examples of audio file formats include AAC, MP3, WAV, and PCM.
Textual Version FormatsSimilarly, the text data to which the audio data is mapped may be stored in one of many document file formats. Non-limiting examples of document file formats include DOC, TXT, PDF, RTF, HTML, XHTML, and EPUB.
A typical EPUB document is accompanied by a file that (a) lists each XHTML content document, and (b) indicates an order of the XHTML content documents. For example, if a book comprises 20 chapters, then an EPUB document for that book may have 20 different XHTML documents, one for each chapter. A file that accompanies the EPUB document identifies an order of the XHTML documents that corresponds to the order of the chapters in the book. Thus, a single (logical) document (whether an EPUB document or another type of document) may comprise multiple data items or files.
The words or characters reflected in the text data may be in one or multiple languages. For example, one portion of the text data may be in English while another portion of the text data may be in French. Although examples of English words are provided herein, embodiments of the invention may be applied to other languages, including character-based languages.
Audio and Text Locations in MappingAs described herein, a mapping comprises a set of mapping records, where each mapping record associates an audio location with a text location.
Each audio location identifies a location in audio data. An audio location may indicate an absolute location within the audio data, a relative location within the audio data, or a combination of an absolute location and a relative location. As an example of an absolute location, an audio location may indicate a time offset (e.g., 04:32:24 indicating 4 hours, 32 minutes, 24 seconds) into the audio data, or a time range, as indicated above in Example A. As an example of a relative location, an audio location may indicate a chapter number, a paragraph number, and a line number. As an example of a combination of an absolute location and a relative location, the audio location may indicate a chapter number and a time offset into the chapter indicated by the chapter number.
Similarly, each text location identifies a location in text data, such as a textual version of a work. A text location may indicate an absolute location within the textual version of the work, a relative location within the textual version of the work, or a combination of an absolute location and a relative location. As an example of an absolute location, a text location may indicate a byte offset into the textual version of the work and/or an “anchor” within the textual version of the work. An anchor is metadata within the text data that identifies a specific location or portion of text. An anchor may be stored separate from the text in the text data that is displayed to an end-user or may be stored among the text that is displayed to an end-user. For example, text data may include the following sentence: “Why did the chicken <i name=“123”/>cross the road?” where “<i name=“123”/>” is the anchor. When that sentence is displayed to a user, the user only sees “Why did the chicken cross the road?” Similarly, the same sentence may have multiple anchors as follows: “<i name=“123”/>Why <i name=“124”/>did <i name=“125”/>the <i name=“126”/>chicken <i name=“127”/>cross <i name=“128”/>the <i name=“129”/>road?” In this example, there is an anchor prior to each word in the sentence.
As an example of a relative location, a text location may indicate a page number, a chapter number, a paragraph number, and/or a line number. As an example of a combination of an absolute location and a relative location, a text location may indicate a chapter number and an anchor into the chapter indicated by the chapter number.
Examples of how to represent a text location and an audio location are provided in the specification entitled “EPUB Media Overlays 3.0,” which defines a usage of SMIL (Synchronized Multimedia Integration Language), an EPUB Style Sheet, and an EPUB Content Document. An example of an association that associates a text location with an audio location and that is provided in the specification is as follows:
In Example A, the “par” element includes two child elements: a “text” element and an “audio” element. The text element comprises an attribute “src” that identifies a particular sentence within an XHTML document that contains content from the first chapter of a book. The audio element comprises a “src” attribute that identifies an audio file that contains an audio version of the first chapter of the book, a “clipBegin” attribute that identifies where an audio clip within the audio file begins, and a “clipEnd” attribute that identifies where the audio clip within the audio file ends. Thus, seconds 23 through 45 in the audio file correspond to the first sentence in Chapter 1 of the book.
Creating a Mapping Between Text and AudioAccording to an embodiment, a mapping between a textual version of a work and an audio version of the same work is automatically generated. Because the mapping is generated automatically, the mapping may use much finer granularity than would be practical using manual text-to-audio mapping techniques. Each automatically-generated text-to-audio mapping includes multiple mapping records, each of which associates a text location in the textual version with an audio location in the audio version.
Step 130 may involve the speech-to-text analyzer comparing the generated text with text in the textual version of the work to determine where, within the textual version of the work, the generated text is located. For each portion of generated text that is found in the textual version of the work, the speech-to-text analyzer associates (1) an audio location that indicates where, within the audio data, the corresponding portion of audio data is found with (2) a text location that indicates where, within the textual version of the work, the portion of text is found.
Textual ContextEvery document has a “textual context”. The textual context of a textual version of a work includes intrinsic characteristics of the textual version of the work (e.g. the language the textual version of the work is written in, the specific words that textual version of the work uses, the grammar and punctuation that textual version of the work uses, the way the textual version of the work is structured, etc.) and extrinsic characteristics of the work (e.g. the time period in which the work was created, the genre to which the work belongs, the author of the work, etc.)
Different works may have significantly different textual contexts. For example, the grammar used in a classic English novel may be very different that the grammar of modern poetry. Thus, while a certain word order may follow the rules of one grammar, that same word order may violate the rules of another grammar. Similarly, the grammar used in both a classic English novel and modern poetry may differ from the grammar (or lack thereof) employed in a text message sent from one teenager to another.
As mentioned above, one technique described herein automatically creates a fine granularity mapping between the audio version of a work and the textual version of the same work by performing a speech-to-text conversion of the audio version of the work. In an embodiment, the textual context of a work is used to increase the accuracy of the speech-to-text analysis that is performed on the audio version of the work. For example, in order to determine the grammar employed in a work, the speech-to-text analyzer (or another process) may analyze the textual version of the work prior to performing a speech-to-text analysis. The speech-to-text analyzer may then make use of the grammar information thus obtained to increase the accuracy of the speech-to-text analysis of the audio version of the work.
Instead of or in addition to automatically determining the grammar of a work based on the textual version of the work, a user may provide input that identifies one or more rules of grammar that are followed by the author of the work. The rules associated with the identified grammar are input to the speech-to-text analyzer to assist the analyzer in recognizing words in the audio version of the work.
Limiting the Candidate Dictionary Based on Textual VersionTypically, speech-to-text analyzers must be configured or designed to recognize virtually every word in the English language and, optionally, some words in other languages. Therefore, speech-to-text analyzers must have access to a large dictionary of words. The dictionary from which a speech-to-text analyzer selects words during a speech-to-text operation is referred to herein as the “candidate dictionary” of the speech-to-text analyzer. The number of unique words in a typical candidate dictionary is approximately 500,000.
In an embodiment, text from the textual version of a work is taken into account when performing the speech-to-text analysis of the audio version of the work. Specifically, in one embodiment, during the speech-to-text analysis of an audio version of a work, the candidate dictionary used by the speech-to-text analyzer is restricted to the specific set of words that are in the text version of the work. In other words, the only words that are considered to be “candidates” during the speech-to-text operation performed on an audio version of a work are those words that actually appear in the textual version of the work.
By limiting the candidate dictionary used in the speech-to-text translation of a particular work to those words that appear in the textual version of the work, the speech-to-text operation may be significantly improved. For example, assume that the number of unique words in a particular work is 20,000. A conventional speech-to-text analyzer may have difficulty determining to which specific word, of a 500,000 word candidate dictionary, a particular portion of audio corresponds. However, that same portion of audio may unambiguously correspond to one particular word when only the 20,000 unique words that are in the textual version of the work are considered. Thus, with such a much smaller dictionary of possible words, the accuracy of the speech-to-text analyzer may be significantly improved.
Limiting the Candidate Dictionary Based on Current PositionTo improve accuracy, the candidate dictionary may be restricted to even fewer words than all of the words in the textual version of the work. In one embodiment, the candidate dictionary is limited to those words found in a particular portion of the textual version of the work. For example, during a speech-to-text translation of a work, it is possible to approximately track the “current translation position” of the translation operation relative to the textual version of the work. Such tracking may be performed, for example, by comparing (a) the text that has been generated during the speech-to-text operation so far, against (b) the textual version of the work.
Once the current translation position has been determined, the candidate dictionary may further restricted based on the current translation position. For example, in one embodiment, the candidate dictionary is limited to only those words that appear, within the textual version of the work, after the current translation position. Thus, words that are found prior to the current translation position, but not thereafter, are effectively removed from the candidate dictionary. Such removal may increase the accuracy of the speech-to-text analyzer, since the smaller the candidate dictionary, the less likely the speech-to-text analyzer will translate a portion of audio data to the wrong word.
As another example, prior to a speech-to-text analysis, an audio book and a digital book may be divided into a number of segments or sections. The audio book may be associated with an audio section mapping and the digital book may be associated with a text section mapping. For example, the audio section mapping and the text section mapping may identify where each chapter begins or ends. These respective mappings may be used by a speech-to-text analyzer to limit the candidate dictionary. For example, if the speech-to-text analyzer determines, based on the audio section mapping, that the speech-to-text analyzer is analyzing the 4th chapter of the audio book, then the speech-to-text analyzer uses the text section mapping to identify the 4th chapter of the digital book and limit the candidate dictionary to the words found in the 4th chapter.
In a related embodiment, the speech-to-text analyzer employs a sliding window that moves as the current translation position moves. As the speech-to-text analyzer is analyzing the audio data, the speech-to-text analyzer moves the sliding window “across” the textual version of the work. The sliding window indicates two locations within the textual version of the work. For example, the boundaries of the sliding window may be (a) the start of the paragraph that precedes the current translation position and (b) the end of the third paragraph after the current translation position. The candidate dictionary is restricted to only those words that appear between those two locations.
While a specific example was given above, the window may span any amount of text within the textual version of the work. For example, the window may span an absolute amount of text, such as 60 characters. As another example, the window may span a relative amount of text from the textual version of the work, such as ten words, three “lines” of text, 2 sentences, or 1 “page” of text. In the relative amount scenario, the speech-to-text analyzer may use formatting data within the textual version of the work to determine how much of the textual version of the work constitutes a line or a page. For example, the textual version of a work may comprise a page indicator (e.g., in the form of an HTML or XML tag) that indicates, within the content of the textual version of the work, the beginning of a page or the ending of a page.
In an embodiment, the start of the window corresponds to the current translation position. For example, the speech-to-text analyzer maintains a current text location that indicates the most recently-matched word in the textual version of the work and maintains a current audio location that indicates the most recently-identified word in the audio data. Unless the narrator (whose voice is reflected in the audio data) misreads text of the textual version of the work, adds his/her own content, or skips portions of the textual version of the work during the recording, the next word that the speech-to-text analyzer detects in the audio data (i.e., after the current audio location) is most likely the next word in the textual version of the work (i.e., after the current text location). Maintaining both locations may significantly increase the accuracy of the speech-to-text translation.
Creating a Mapping Using Audio-to-Audio CorrelationIn an embodiment, a text-to-speech generator and an audio-to-text correlator are used to automatically create a mapping between the audio version of a work and the textual version of a work.
Text-to-speech generator 220 generates audio data 230 based on document 210. During the generation of the audio data 230, text-to-speech generator 220 (or another component not shown) creates an audio-to-document mapping 240. Audio-to-document mapping 240 maps, multiple text locations within document 210 to corresponding audio locations within generated audio data 230.
For example, assume that text-to-speech generator 220 generates audio data for a word located at location Y within document 210. Further assume that the audio data that was generated for the work is located at a location X within audio data 230. To reflect the correlation between the location of the word within the document 210 and the location of the corresponding audio in the audio data 230, a mapping would be created between location X and location Y.
Because text-to-speech generator 220 knows where a word or phrase occurs in document 210 when a corresponding word or phrase of audio is generated, each mapping between the corresponding words or phrases can be easily generated.
Audio-to-text correlator 260 accepts, as input, generated audio data 230, audio book 250, and audio-to-document mapping 240. Audio-to-text correlator 260 performs two main steps: an audio-to-audio correlation step and a look-up step. For the audio-to-audio correlation step, audio-to-text correlator 260 compares generated audio data 230 with audio book 250 to determine the correlation between portions of audio data 230 and portions of audio book 250. For example, audio-to-text correlator 260 may determine, for each word represented in audio data 230, the location of the corresponding word in audio book 250.
The granularity at which audio data 230 is divided, for the purpose of establishing correlations, may vary from implementation to implementation. For example, a correlation may be established between each word in audio data 230 and each corresponding word in audio book 250. Alternatively, a correlation may be established based on fixed-duration time intervals (e.g. one mapping for every 1 minute of audio). In yet another alternative, a correlation may be established for portions of audio established based on other criteria, such as at paragraph or chapter boundaries, significant pauses (e.g., silence of greater than 3 seconds), or other locations based on data in audio book 250, such as audio markers within audio book 250.
After a correlation between a portion of audio data 230 and a portion of audio book 250 is identified, audio-to-text correlator 260 uses audio-to-document mapping 240 to identify a text location (indicated in mapping 240) that corresponds to the audio location within generated audio data 230. Audio-to-text correlator 260 then associates the text location with the audio location within audio book 250 to create a mapping record in document-to-audio mapping 270.
For example, assume that a portion of audio book 250 (located at location Z) matches the portion of generated audio data 230 that is located at location X. Based on a mapping record (in audio-to-document mapping 240) that correlates location X to location Y within document 210, a mapping record in document-to-audio mapping 270 would be created that correlates location Z of the audio book 250 with location Y within document 210.
Audio-to-text correlator 260 repeatedly performs the audio-to-audio correlation and look-up steps for each portion of audio data 230. Therefore, document-to-audio mapping 270 comprises multiple mapping records, each mapping record mapping a location within document 210 to a location within audio book 250.
In an embodiment, the audio-to-audio correlation for each portion of audio data 230 is immediately followed by the look-up step for that portion of audio. Thus, document-to-audio mapping 270 may be created for each portion of audio data 230 prior to proceeding to the next portion of audio data 230. Alternatively, the audio-to-audio correlation step may be performed for many or for all of the portions of audio data 230 before any look-up step is performed. The look-up steps for all portions can be performed in a batch, after all of the audio-to-audio correlations have been established.
Mapping GranularityA mapping has a number of attributes, one of which is the mapping's size, which refers to the number of mapping records in the mapping. Another attribute of a mapping is the mapping's “granularity.” The “granularity” of a mapping refers to the number of mapping records in the mapping relative to the size of the digital work. Thus, the granularity of a mapping may vary from one digital work to another digital work. For example, a first mapping for a digital book that comprises 200 “pages” includes a mapping record only for each paragraph in the digital book. Thus, the first mapping may comprise 1000 mapping records. On the other hand, a second mapping for a digital “children's” book that comprises 20 pages includes a mapping record for each word in the children's book. Thus, the second mapping may comprise 800 mapping records. Even though the first mapping comprises more mapping records than the second mapping, the granularity of the second mapping is finer than the granularity of the first mapping.
In an embodiment, the granularity of a mapping may be dictated based on input to a speech-to-text analyzer that generates the mapping. For example, a user may specify a specific granularity before causing a speech-to-text analyzer to generate a mapping. Non-limiting examples of specific granularities include:
word granularity (i.e., an association for each word),
sentence granularity (i.e., an association for each sentence),
paragraph granularity (i.e., an association for each paragraph),
10-word granularity (i.e., a mapping for each 10 word portion in the digital work), and
10-second granularity (i.e., a mapping for each 10 seconds of audio).
As another example, a user may specify the type of digital work (e.g., novel, children's book, short story) and the speech-to-text analyzer (or another process) determines the granularity based on the work's type. For example, a children's book may be associated with word granularity while a novel may be associated with sentence granularity.
The granularity of a mapping may even vary within the same digital work. For example, a mapping for the first three chapters of a digital book may have sentence granularity while a mapping for the remaining chapters of the digital book have word granularity.
On-The-Fly Mapping Generation During Text-to-Audio TransitionsWhile an audio-to-text mapping will, in many cases, be generated prior to a user needing to rely on one, in one embodiment, an audio-to-text mapping is generated at runtime or after a user has begun to consume the audio data and/or the text data on the user's device. For example, a user reads a textual version of a digital book using a tablet computer. The tablet computer keeps track of the most recent page or section of the digital book that the tablet computer has displayed to the user. The most recent page or section is identified by a “text bookmark.”
Later, the user selects to play an audio book version of the same work. The playback device may be the same tablet computer on which the user was reading the digital book or another device. Regardless of the device upon which the audio book is to be played, the text bookmark is retrieved, and a speech-to-text analysis is performed relative to at least a portion of the audio book. During the speech-to-text analysis, “temporary” mapping records are generated to establish a correlation between the generated text and the corresponding locations within the audio book.
Once the text and correlation records have been generated, a text-to-text comparison is used to determine the generated text that corresponds to the text bookmark. Then, the temporary mapping records are used to identify the portion of the audio book that corresponds to the portion of generated text that corresponds to the text bookmark. Playback of the audio book is then initiated from that position.
The portion of the audio book on which the speech-to-text analysis is performed may be limited to the portion that corresponds to the text bookmark. For example, an audio section mapping may already exist that indicates where certain portions of the audio book begin and/or end. For example, an audio section mapping may indicate where each chapter begins, where one or more pages begin, etc. Such an audio section mapping may be helpful to determine where to begin the speech-to-text analysis so that a speech-to-text analysis on the entire audio book is not required to be performed. For example, if the text bookmark indicates a location within the 12th chapter of the digital book and an audio section mapping associated with the audio data identifies where the 12th chapter begins in the audio data, then a speech-to-text analysis is not required to be performed on any of the first 11 chapters of the audio book. For example, the audio data may consist of 20 audio files, one audio file for each chapter. Therefore, only the audio file that corresponds to the 12th chapter is input to a speech-to-text analyzer.
On-the-Fly Mapping Generation During Audio-to-Text TransitionsMapping records can be generated on-the-fly to facilitate audio-to-text transitions, as well as text-to-audio transitions. For example, assume that a user is listening to an audio book using a smart phone. The smart phone keeps track of the current location within the audio book that is being played. The current location is identified by an “audio bookmark.” Later, the user picks up a tablet computer and selects a digital book version of the audio book to display. The tablet computer receives the audio bookmark (e.g., from a central server that is remote relative to the tablet computer and the smart phone), performs a speech-to-text analysis of at least a portion of the audio book, and identifies, within the audio book, a portion that corresponds to a portion of text within a textual version of the audio book that corresponds to the audio bookmark. The tablet computer then begins displaying the identified portion within the textual version.
The portion of the audio book on which the speech-to-text analysis is performed may be limited to the portion that corresponds to the audio bookmark. For example, a speech-to-text analysis is performed on a portion of the audio book that spans one or more time segments (e.g., seconds) prior to the audio bookmark in the audio book and/or one or more time segments after the audio bookmark in the audio book. The text produced by the speech-to-text analysis on that portion is compared to text in the textual version to locate where the series of words or phrases in the produced text match text in the textual version.
If there exists a text section mapping that indicates where certain portions of the textual version begin or end and the audio bookmark can be used to identify a section in the text section mapping, then much of the textual version need not be analyzed in order to locate where the series of words or phrases in the produced text match text in the textual version. For example, if the audio bookmark indicates a location within in the 3rd chapter of the audio book and a text section mapping associated with the digital book identifies where the 3rd chapter begins in the textual version, then a speech-to-text analysis is not required to be performed on any of the first two chapters of the audio book or on any of the chapters of the audio book after the 3rd chapter.
Overview of Use of Audio-to-Text MappingsAccording to one approach, a mapping (whether created manually or automatically) is used to identify the locations within an audio version of a digital work (e.g., an audio book) that correspond to locations within a textual version of the digital work (e.g., an e-book). For example, a mapping may be used to identify a location within an e-book based on a “bookmark” established in an audio book. As another example, a mapping may be used to identify which displayed text corresponds to an audio recording of a person reading the text as the audio recording is being played and cause the identified text to be highlighted. Thus, while an audio book is being played, a user of an e-book reader may follow along as the e-book reader highlights the corresponding text. As another example, a mapping may be used to identify a location in audio data and play audio at that location in response to input that selects displayed text from an e-book. Thus, a user may select a word in an e-book, which selection causes audio that corresponds to that word to be played. As another example, a user may create an annotation while “consuming” (e.g., reading or listening to) one version of a digital work (e.g., an e-book) and cause the annotation to be consumed while the user is consuming another version of the digital work (e.g., an audio book). Thus, a user can make notes on a “page” of an e-book and may view those notes while listening to an audio book of the e-book. Similarly, a user can make a note while listening to an audio book and then can view that note when reading the corresponding e-book.
At step 310, location data that indicates a specified location within a first media item is obtained. The first media item may be a textual version of a work or audio data that corresponds to a textual version of the work. This step may be performed by a device (operated by a user) that consumes the first media item. Alternatively, the step may be performed by a server that is located remotely relative to the device that consumes the first media item. Thus, the device sends the location data to the server over a network using a communication protocol.
At step 320, a mapping is inspected to determine a first media location that corresponds to the specified location. Similarly, this step may be performed by a device that consumes the first media item or by a server that is located remotely relative to the device.
At step 330, a second media location that corresponds to the first media location and that is indicated in the mapping is determined. For example, if the specified location is an audio “bookmark”, then the first media location is an audio location indicated in the mapping and the second media location is a text location that is associated with the audio location in the mapping. Similarly, For example, if the specified location is a text “bookmark”, then the first media location is a text location indicated in the mapping and the second media location is an audio location that is associated with the text location in the mapping.
At step 340, the second media item is processed based on the second media location. For example, if the second media item is audio data, then the second media location is an audio location and is used as a current playback position in the audio data. As another example, if the second media item is a textual version of a work, then the second media location is a text location and is used to determine which portion of the textual version of the work to display.
Examples of using process 300 in specific scenarios are provided below.
Architecture OverviewEach of the example scenarios mentioned above and described in detail below may involve one or more computing devices.
As depicted in
Similarly, audio media player 414 is configured to process audio data and cause device 410 to generate audio (e.g., via speakers on device 410, not shown). Thus, if digital media item 402 is an audio book, then audio media player 414 may be configured to process digital media item 402, as long as digital media item 402 is in an audio format that audio media player 414 is configured to process. Whether item 402 is an e-book or an audio book, item 402 may comprise multiple files, whether audio files or text files.
Device 430 similarly stores a digital media item 404 and executes an audio media player 432 that is configured to process audio data and cause device 430 to generate audio. Device 430 may execute one or more other media players (not shown) that are configured to process other types of media, such as video and text.
Intermediary device 420 stores a mapping 406 that maps audio locations within audio data to text location in text data. For example, mapping 406 may map audio locations within digital media item 404 to text locations within digital media item 402. Although not depicted in
Also, intermediary device 420 may store digital media items that users may access via their respective devices. Thus, instead of storing a local copy of a digital media item, a device (e.g., device 430) may request the digital media item from intermediary device 420.
Additionally, intermediary device 420 may store account data that associates one or more devices of a user with a single account. Thus, such account data may indicate that devices 410 and 430 are registered by the same user under the same account. Intermediary device 420 may also store account-item association data that associates an account with one or more digital media items owned (or purchased) by a particular user. Thus, intermediary device 420 may verify that device 430 may access a particular digital media item by determining whether the account-item association data indicates that device 430 and the particular digital media item are associated with the same account.
Although only two end-user devices are depicted, an end-user may own and operate more or less devices that consume digital media items, such as e-books and audio books. Similarly, although only a single intermediary device 420 is depicted, the entity that owns and operates intermediary device 420 may operate multiple devices, each of which provide the same service or may operate together to provide a service to the user of end-user devices 410 and 430.
Communication between intermediary device 420 and end-user devices 410 and 430 is made possible via network 440. Network 440 may be implemented by any medium or mechanism that provides for the exchange of data between various computing devices. Examples of such a network include, without limitation, a network such as a Local Area Network (LAN), Wide Area Network (WAN), Ethernet or the Internet, or one or more terrestrial, satellite, or wireless links. The network may include a combination of networks such as those described. The network may transmit data according to Transmission Control Protocol (TCP), User Datagram Protocol (UDP), and/or Internet Protocol (IP).
Storage Location of MappingA mapping may be stored separate from the text data and the audio data from which the mapping was generated. For example, as depicted in
Additionally or alternatively, a mapping may be stored as part of the corresponding text data. For example, mapping 406 may be stored in digital media item 402. However, even if the mapping is stored as part of the text data, the mapping may not be displayed to an end-user that consumes the text data. Additionally or alternatively still, a mapping may be stored as part of the audio data. For example, mapping 406 may be stored in digital media item 404.
Bookmark Switching“Bookmark switching” refers to establishing a specified location (or “bookmark”) in one version of a digital work and using the bookmark to find the corresponding location within another version of the digital work. There are two types of bookmark switching: text-to-audio (TA) bookmark switching and audio-to-text (AT) bookmark switching. TA bookmark switching involves using a text bookmark established in an e-book to identify a corresponding audio location in an audio book. Conversely, another type of bookmark switching referred to herein as AT bookmark switching involves using an audio bookmark established in an audio book to identify a corresponding text location within an e-book.
Text-to-Audio Bookmark SwitchingAt step 502, a text media player 412 (e.g., an e-reader) determines a text bookmark within digital media item 402 (e.g., a digital book). Device 410 displays content from digital media item 402 to a user of device 410.
The text bookmark may be determined in response to input from the user. For example, the user may touch an area on a touch screen of device 410. Device 410's display, at or near that area, displays one or more words. In response to the input, the text media player 412 determines the one or more words that are closest to the area. The text media player 412 determines the text bookmark based on the determined one or more words.
Alternatively, the text bookmark may be determined based on the last text data that was displayed to the user. For example, the digital media item 402 may comprise 200 electronic “pages” and page 110 was the last page that was displayed. Text media player 412 determines that page 110 was the last page that was displayed. Text media player 412 may establish page 110 as the text bookmark or may establish a point at the beginning of page 110 as the text bookmark, since there may be no way to know where the user stopped reading. It may be safe to assume that the user at least read the last sentence on page 109, which sentence may have ended on page 109 or on page 110. Therefore, the text media player 412 may establish the beginning of the next sentence (which begins on page 110) as the text bookmark. However, if the granularity of the mapping is at the paragraph level, then text media player 412 may establish the beginning of the last paragraph on page 109. Similarly, if the granularity of the mapping is at the sentence level, then text media player 412 may establish the beginning of the chapter that includes page 110 as the text bookmark.
At step 504, text media player 412 sends, over network 440 to intermediary device 420, data that indicates the text bookmark. Intermediary device 420 may store the text bookmark in association with device 410 and/or an account of the user of device 410. Previous to step 502, the user may have established an account with an operator of intermediary device 420. The user then registered one or more devices, including device 410, with the operator. The registration caused each of the one or more devices to be associated with the user's account.
One or more factors may cause the text media player 412 to send the text bookmark to intermediary device 420. Such factors may include the exiting (or closing down) of text media player 412, the establishment of the text bookmark by the user, or an explicit instruction by the user to save the text bookmark for use when listening to the audio book that corresponds to the textual version of the work for which the text bookmark is established.
As noted previously, intermediary device 420 has access to (e.g., stores) mapping 406, which, in this example, maps multiple audio locations in digital media item 404 with multiple text locations within digital media item 402.
At step 506, intermediary device 420 inspects mapping 406 to determine a particular text location, of the multiple text locations, that corresponds to the text bookmark. The text bookmark may not exactly match any of the multiple text locations in mapping 406. However, intermediary device 420 may select the text location that is closest to the text bookmark. Alternatively, intermediary device 420 may select the text location that is immediately before the text bookmark, which text location may or may not be the closest text location to the text bookmark. For example, if the text bookmark indicates 5th chapter, 3rd paragraph, 5th sentence and the closest text locations in mapping 406 are (1) 5th chapter, 3rd paragraph, 1st sentence and (2), 5th chapter, 3rd paragraph, 6th sentence, then the text location (1) is selected.
At step 508, once the particular text location in the mapping is identified, intermediary device 420 determines a particular audio location, in mapping 406, that corresponds to the particular text location.
At step 510, intermediary device 420 sends the particular audio location to device 430, which, in this example, is different than device 410. For example, device 410 may be a tablet computer and the device 430 may be a smart phone. In a related embodiment, device 430 is not involved. Thus, intermediary device 420 may send the particular audio location to device 410.
Step 510 may be performed automatically, i.e., in response to intermediary device 420 determining the particular audio location. Alternatively, step 510 or step 506) may be performed in response to receiving, from device 430, an indication that device 430 is about to process digital media item 404. The indication may be a request for an audio location that corresponds to the text bookmark.
At step 512, audio media player 432 establishes the particular audio location as a current playback position of the audio data in digital media item 404. This establishment may be performed in response to receiving the particular audio location from intermediary device 420. Because the current playback position becomes the particular audio location, audio media player 432 is not required to play any of the audio that precedes the particular audio location in the audio data. For example, if the particular audio location indicates 2:56:03 (2 hours, 56 minutes, and 3 seconds), then audio media player 432 establishes that time in the audio data as the current playback position. Thus, if the user of device 430 selects a “play” button (whether graphical or physical) on device 430, then audio media player 430 begins processing the audio data at that 2:56:03 mark.
In an alternative embodiment, device 410 stores mapping 406 (or a copy thereof). Therefore, in place of steps 504-508, text media player 412 inspects mapping 406 to determine a particular text location, of the multiple text locations, that corresponds to the text bookmark. Then, text media player 412 determines a particular audio location, in mapping 406, that corresponds to the particular text location. The text media player 412 may then cause the particular audio location to be sent to intermediary device 420 to allow device 430 to retrieve the particular audio location and establish a current playback position in the audio data to be the particular audio location. Text media player 412 may also cause the particular text location (or text bookmark) to be sent to intermediary device 420 to allow device 410 (or another device, not shown) to later retrieve the particular text location to allow another text media player executing on the other device to display a portion (e.g., a page) of another copy of digital media item 402, where the portion corresponds to the particular text location.
In another alternative embodiment, intermediary device 420 and device 430 are not involved. Thus, steps 504 and 510 are not performed. Thus, device 410 performs all other steps in
At step 552, audio media player 432 determines an audio bookmark within digital media item 404 (e.g., an audio book).
The audio bookmark may be determined in response to input from the user. For example, the user may stop the playback of the audio data, for example, by selecting a “stop” button that is displayed on a touch screen of device 430. Audio media player 432 determines the location within audio data of digital media item 404 that corresponds to where playback stopped. Thus, the audio bookmark may simply be the last place where the user stopped listening to the audio generated from digital media item 404. Additionally or alternatively, the user may select one or more graphical buttons on the touch screen of device 430 to establish a particular location within digital media item 404 as the audio bookmark. For example, device 430 displays a timeline that corresponds to the length of the audio data in digital media item 404. The user may select a position on the timeline and then provide one or more additional inputs that are used by audio media player 432 to establish the audio bookmark.
At step 554, device 430 sends, over network 440 to intermediary device 420, data that indicates the audio bookmark. The intermediary device 420 may store the audio bookmark in association with device 430 and/or an account of the user of device 430. Previous to step 552, the user established an account with an operator of intermediary device 420. The user then registered one or more devices, including device 430, with the operator. The registration caused each of the one or more devices to be associated with the user's account.
Intermediary device 420 also has access to (e.g., stores) mapping 406. Mapping 406 maps multiple audio locations in the audio data of digital media item 404 with multiple text locations within text data of digital media item 402.
One or more factors may cause audio media player 432 to send the audio bookmark to intermediary device 420. Such factors may include the exiting (or closing down) of audio media player 432, the establishment of the audio bookmark by the user, or an explicit instruction by the user to save the audio bookmark for use when displaying portions of the textual version of the work (reflected in digital media item 402) that corresponds to digital media item 404, for which the audio bookmark is established.
At step 556, intermediary device 420 inspects mapping 406 to determine a particular audio location, of the multiple audio locations, that corresponds to the audio bookmark. The audio bookmark may not exactly match any of the multiple audio locations in mapping 406. However, intermediary device 420 may select the audio location that is closest to the audio bookmark. Alternatively, intermediary device 420 may select the audio location that is immediately before the audio bookmark, which audio location may or may not be the closest audio location to the audio bookmark. For example, if the audio bookmark indicates 02:43:19 (or 2 hours, 43 minutes, and 19 seconds) and the closest audio locations in mapping 406 are (1) 02:41:07 and (2), 0:43:56, then the audio location (1) is selected, even though audio location (2) is closest to the audio bookmark.
At step 558, once the particular audio location in the mapping is identified, intermediary device 420 determines a particular text location, in mapping 406, that corresponds to the particular audio location.
At step 560, intermediary device 420 sends the particular text location to device 410, which, in this example, is different than device 430. For example, device 410 may be a tablet computer and device 430 may be a smart phone that is configured to process audio data and generate audible sounds.
Step 560 may be performed automatically, i.e., in response to intermediary device 420 determining the particular text location. Alternatively, step 560 (or step 556) may be performed in response to receiving, from device 410, an indication that device 410 is about to process the digital media item 402. The indication may be a request for a text location that corresponds to the audio bookmark.
At step 562, text media player 412 displays information about the particular text location. Step 562 may be performed in response to receiving the particular text location from intermediary device 420. Device 410 is not required to display any of the content that precedes the particular text location in the textual version of the work reflected in digital media item 402. For example, if the particular text location indicates Chapter 3, paragraph 2, sentence 4, then device 410 displays a page that includes that sentence. Text media player 412 may cause a marker to be displayed at the particular text location in the page that visually indicates, to a user of device 410, where to begin reading in the page. Thus, the user is able to immediately read the textual version of the work beginning at a location that corresponds to the last words spoken by a narrator in the audio book.
In an alternative embodiment, the device 410 stores mapping 406. Therefore, in place of steps 556-560, after step 554 (wherein the device 430 sends data that indicates the audio bookmark to intermediary device 420), intermediary device 420 sends the audio bookmark to device 410. Then, text media player 412 inspects mapping 406 to determine a particular audio location, of the multiple audio locations, that corresponds to the audio bookmark. Then, text media player 412 determines a particular text location, in mapping 406, that corresponds to the particular audio location. This alternative process then proceeds to step 562, described above.
In another alternative embodiment, intermediary device 420 is not involved. Thus, steps 554 and 560 are not performed. Thus, device 430 performs all other steps in
In an embodiment, text from a portion of a textual version of a work is highlighted or “lit up” while audio data that corresponds to the textual version of the work is played. As noted previously, the audio data is an audio version of a textual version of the work and may reflect a reading, of text from the textual version, by a human user. As used herein, “highlighting” text refers to a media player (e.g., an “e-reader”) visually distinguishing that text from other text that is concurrently displayed with the highlighted text. Highlighting text may involve changing the font of the text, changing the font style of the text (e.g., italicize, bold, underline), changing the size of the text, changing the color of the text, changing the background color of the text, or creating an animation associated with the text. An example of creating an animation is causing the text (or background of the text) to blink on and off or to change colors. Another example of creating an animation is creating a graphic to appear above, below, or around the text. For example, in response to the word “toaster” being played and detected by a media player, the media player displays a toaster image above the word “toaster” in the displayed text. Another example of an animation is a bouncing ball that “bounces” on a portion of text (e.g., word, syllable, or letter) when that portion is detected in audio data that is played.
At step 610, the current playback position (which is constantly changing) of audio data of the audio version is determined. This step may be performed by a media player executing on a user's device. The media player processes the audio data to generate audio for the user.
At step 620, based on the current playback position, a mapping record in a mapping is identified. The current playback position may match or nearly match the audio location identified in the mapping record.
Step 620 may be performed by the media player if the media player has access to a mapping that maps multiple audio locations in the audio data with multiple text locations in the textual version of the work. Alternatively, step 620 may be performed by another process executing on the user's device or by a server that receives the current playback position from the user's device over a network.
At step 630, the text location identified in the mapping record is identified.
At step 640, a portion of the textual version of the work that corresponds to the text location is caused to be highlighted. This step may be performed by the media player or another software application executing on the user's device. If a server performs the look-up steps (620 and 630), then step 640 may further involve the server sending the text location to the user's device. In response, the media player, or another software application, accepts the text location as input and causes the corresponding text to be highlighted.
In an embodiment, different text locations that are identified, by the media player, in the mapping are associated with different types of highlighting. For example, one text location in the mapping may be associated with the changing of the font color from black to red while another text location in the mapping may be associated with an animation, such as a toaster graphic that shows a piece of toast “popping” out of toaster. Therefore, each mapping record in the mapping may include “highlighting data” that indicates how the text identified by the corresponding text location is to be highlighted. Thus, for each mapping record in the mapping that the media player identifies and that includes highlighting data, the media player uses the highlighting data to determine how to highlight the text. If a mapping record does not include highlighting data, then the media player may not highlight the corresponding text. Alternatively, if an mapping record in the mapping does not include highlighting data, then the media player may use a “default” highlight technique (e.g., bolding the text) to highlight the text.
Highlighting Text Based on Audio InputAt step 710, audio input is received. The audio input may be based on a user reading aloud text from a textual version of a work. The audio input may be received by a device that displays a portion of the textual version. The device may prompt the user to read aloud a word, phrase, or entire sentence. The prompt may be visual or audio. As an example of a visual prompt, the device may cause the following text to be displayed: “Please read the underlined text” while or immediately before the device displays a sentence that is underlined. As an example of an audio prompt, the device may cause a computer-generated voice to read “Please read the underlined text” or cause a pre-recorded human voice to be played, where the pre-recorded human voice provides the same instruction.
At step 720, a speech-to-text analysis is performed on the audio input to detect one or more words reflected in the audio input.
At step 730, for each detected word reflected in the audio input, that detected word is compared to a particular set of words. The particular set of words may be all the words that are currently displayed by a computing device (e.g., an e-reader). Alternatively, the particular set of words may be all the words that the user was prompted to read.
At step 740, for each detected word that matches a word in the particular set, the device causes that matching word to be highlighted.
The steps depicted in process 700 may be performed by a single computing device that displays text from a textual version of a work. Alternatively, the steps depicted in process 700 may be performed by one or more computing devices that are different than the computing device that displays text from the textual version. For example, the audio input from a user in step 710 may be sent from the user's device over a network to a network server that performs the speech-to-text analysis. The network server may then send highlight data to the user's device to cause the user's device to highlight the appropriate text.
Playing Audio in Response to Text SelectionIn an embodiment, a user of a media player that displays portions of a textual version of a work may select portions of displayed text and cause the corresponding audio to be played. For example, if a displayed word from the digital book is “donut” and the user selects that word (e.g., by touching a portion of the media player's touch screen that displays that word), then the audio of “donut” may be played.
A mapping that maps text locations in a textual version of the work with audio locations in audio data is used to identify the portion of the audio data that corresponds to the selected text. The user may select a single word, a phrase, or even one or more sentences. In response to input that selects a portion of the displayed text, the media player may identify one or more text locations. For example, the media player may identify a single text location that corresponds to the selected portion, even if the selected portion comprises multiple lines or sentences. The identified text location may correspond to the beginning of the selected portion. As another example, the media player may identify a first text location that corresponds to the beginning of the selected portion and a second text location that corresponds to the ending of the selected portion.
The media player uses the identified text location to look up a mapping record in the mapping that indicates a text location that is closest (or closest prior) to the identified text location. The media player uses the audio location indicated in the mapping record to identify where, in the audio data, to begin processing the audio data in order to generate audio. If only a single text location is identified, then only the word or sounds at or near the audio location may be played. Thus, after the word or sounds are played, the media player ceases to play any more audio. Alternatively, the media player begins playing at or near the audio location and does not cease playing the audio that follows the audio location until (a) the end of the audio data is reached, (b) further input from the user (e.g., selection of a “stop” button), or (c) a pre-designated stopping point in the audio data (e.g., end of a page or chapter that requires further input to proceed).
If the media player identifies two text locations based on the selected portion, then two audio locations are identified and may be used to identify where to begin playing and where to stop playing the corresponding audio.
In an embodiment, the audio data identified by the audio location may be played slowly (i.e., at a slow playback speed) or continuously without advancing the current playback position in the audio data. For example, if a user of a tablet computer selects the displayed word “two” by touching a touch screen of the tablet computer with his finger and continuously touches the displayed word (i.e., without lifting his finger and without moving his finger to another displayed word), then the tablet computer plays the corresponding audio creating a sound reflected by reading the word “twoooooooooooooooo”.
In a similar embodiment, the speed at which a user drags her finger across displayed text on a touch screen of a media player causes the corresponding audio to be played at the same or similar speed. For example, a user selects the letter “d” of the displayed word “donut” and then slowly moves his finger across the displayed word. In response to this input, the media player identifies the corresponding audio data (using the mapping) and plays the corresponding audio at the same speed at which the user moves his finger. Therefore, the media player creates audio that sounds as if the reader of the text of the textual version of the work pronounced the word “donut” as “dooooooonnnnnnuuuuuut.”
In a similar embodiment, the time that a user “touches” a word displayed on a touch screen dictates how quickly or slowly the audio version of the word is played. For example, a quick tap of a displayed word by the user's finger causes the corresponding audio to be played at a normal speed, whereas the user holding down his finger on the selected word for more than 1 second causes the corresponding audio to be played at ½ the normal speed.
Transferring User AnnotationsIn an embodiment, a user initiates the creation of annotations to one media version (e.g., audio) of a digital work and causes the annotations to be associated with another media version (e.g., text) of the digital work. Thus, while an annotation may be created in the context of one type of media, the annotation may be consumed in the context of another type of media. The “context” in which an annotation is created or consumed refers to whether text is being displayed or audio is being played when the creation or consumption occurs.
Although the following examples involve determining a location within audio or text location when an annotation is created, some embodiments of the invention are not so limited. For example, the current playback position within an audio file when an annotation is created in the audio context is not used when consuming the annotation in the text context. Instead, an indication of the annotation may be displayed, by a device, at the beginning or the end of the corresponding textual version or on each “page” of the corresponding textual version. As another example, the text that is displayed when an annotation is created in the text context is not used when consuming the annotation in the audio context. Instead, an indication of the annotation may be displayed, by a device, at the beginning or end of the corresponding audio version or continuously while the corresponding audio version is being played. Additionally or alternatively to a visual indication, an audio indication of the annotation may be played. For example, a “beep” is played simultaneously with the audio track in such a way that both the beep and the audio track can be heard.
At step 802 in
At step 804, text media player 412 determines a text location within a textual version of the work reflected in digital media item 402. The text location is eventually stored in association with an annotation. The text location may be determined in a number of ways. For example, text media player 412 may receive input that selects the text location within the displayed text. The input may be a user touching a touch screen (that displays the text) of device 410 for a period of time. The input may select a specific word, a number of words, the beginning or ending of a page, before or after a sentence, etc. The input may also include first selecting a button, which causes text media player 412 to change to a “create annotation” mode where an annotation may be created and associated with the text location.
As another example of determining a text location, text media player 412 determines the text location automatically (without user input) based on which portion of the textual version of the work (reflected in digital media item 402) is being displayed. For example, if device 410 is displaying page 20 of the textual version of the work, then the annotation will be associated with page 20.
At step 806, text media player 412 receives input that selects a “Create Annotation” button that may be displayed on the touch screen. Such a button may be displayed in response to input in step 804 that selects the text location, where, for example, the user touches the touch screen for a period of time, such as one second.
Although step 804 is depicted as occurring before step 806, alternatively, the selection of the “Create Annotation” button may occur prior to the determination of the text location.
At step 808, text media player 412 receives input that is used to create annotation data. The input may be voice data (such as the user speaking into a microphone of device 410) or text data (such as the user selecting keys on a keyboard, whether physical or graphical). If the annotation data is voice data, text media player 412 (or another process) may perform speech-to-text analysis on the voice data to create a textual version of the voice data.
At step 810, text media player 412 stores the annotation data in association with the text location. Text media player 412 uses a mapping (e.g., a copy of mapping 406) to identify a particular text location, in mapping, that is closest to the text location. Then, using mapping, text media player identifies an audio location that corresponds to the particular text location.
Alternatively to step 810, text media player 412 sends, over network 440 to intermediary device 420, the annotation data and the text location. In response, intermediary device 420 stores the annotation data in association with the text location. Intermediary device 420 uses a mapping (e.g., mapping 406) to identify a particular text location, in mapping 406, that is closest to the text location. Then, using mapping 406, intermediary device 420 identifies an audio location that corresponds to the particular text location. Intermediary device 420 sends the identified audio location over network 440 to device 410. Intermediary device 420 may send the identified audio location in response to a request, from device 410, for certain audio data and/or for annotations associated with certain audio data. For example, in response to a request for an audio book version of “The Tale of Two Cities”, intermediary device 420 determines whether there is any annotation data associated with that audio book and, if so, sends the annotation data to device 410.
Step 810 may also comprise storing date and/or time information that indicates when the annotation was created. This information may be displayed later when the annotation is consumed in the audio context.
At step 812, audio media player 414 plays audio by processing audio data of digital media item 404, which, in this example (although not shown), may be stored on device 410 or may be streamed to device 410 from intermediary device 420 over network 440.
At step 814, audio media player 414 determines when the current playback position in the audio data matches or nearly matches the audio location identified in step 810 using mapping 406. Alternatively, audio media player 414 may cause data that indicates that an annotation is available to be displayed, regardless of where the current playback position is located and without having to play any audio, as indicated in step 812. In other words, step 812 is unnecessary. For example, a user may launch audio media player 414 and cause audio media player 414 to load the audio data of digital media item 404. Audio media player 414 determines that annotation data is associated with the audio data. Audio media player 414 causes information about the audio data (e.g., title, artist, genre, length, etc.) to be displayed without generating any audio associated with the audio data. The information may include a reference to the annotation data and information about a location within the audio data that is associated with the annotation data, where the location corresponds to the audio location identified in step 810.
At step 816, audio media player 414 consumes the annotation data. If the annotation data is voice data, then consuming the annotation data may involve processing the voice data to generate audio or converting the voice data to text data and displaying the text data. If the annotation data is text data, then consuming the annotation data may involve displaying the text data, for example, in a side panel of a GUI that displays attributes of the audio data that is played or in a new window that appears separate from the GUI. Non-limiting examples of attributes include time length of the audio data, the current playback position, which may indicate an absolute location within the audio data (e.g., a time offset) or a relative position within the audio data (e.g., chapter or section number), a waveform of the audio data, and title of the digital work.
At step 852, audio media player 432 processes audio data from digital media item 404 to play audio.
At step 854, audio media player 432 determines an audio location within the audio data. The audio location is eventually stored in association with an annotation. The audio location may be determined in a number of ways. For example, audio media player 432 may receive input that selects the audio location within the audio data. The input may be a user touching a touch screen (that displays attributes of the audio data) of device 430 for a period of time. The input may select an absolute position within a timeline that reflects the length of the audio data or a relative position within the audio data, such as a chapter number and a paragraph number. The input may also comprise first selecting a button, which causes audio media player 432 to change to a “create annotation” mode where an annotation may be created and associated with the audio location.
As another example of determining an audio location, audio media player 432 determines the audio location automatically (without user input) based on which portion of the audio data is being processed. For example, if audio media player 432 is processing a portion of the audio data that corresponds to chapter 20 of a digital work reflected in digital media item 404, then audio media player 432 determines that the audio location is at least be somewhere within chapter 20.
At step 856, audio media player 432 receives input that selects a “Create Annotation” button that may be displayed on the touch screen of device 430. Such a button may be displayed in response to input in step 854 that selects the audio location, where, for example, the user touches the touch screen continuously for a period of time, such as one second.
Although step 854 is depicted as occurring before step 856, alternatively, the selection of the “Create Annotation” button may occur prior to the determination of the audio location.
At step 858, the first media player receives input that is used to create annotation data, similar to step 808.
At step 860, audio media player 432 stores the annotation data in association with the audio location. Audio media player 432 uses a mapping (e.g., mapping 406) to identify a particular audio location, in the mapping, that is closest to the audio location determined in step 854. Then, using the mapping, audio media player 432 identifies a text location that corresponds to the particular audio location.
Alternatively to step 860, audio media player 432 sends, over network 400 to intermediary device 420, the annotation data and the audio location. In response, intermediary device 420 stores the annotation data in association with the audio location. Intermediary device 420 uses mapping 406 to identify a particular audio location, in the mapping, that is closest to the audio location determined in step 854. Then, using mapping 406, intermediary device 420 identifies a text location that corresponds to the particular audio location. Intermediary device 420 sends the identified text location over network 440 to device 410. Intermediary device 420 may send the identified text location in response to a request, from device 410, for certain text data and/or for annotations associated with certain text data. For example, in response to a request for a digital book of “The Grapes of Wrath”, intermediary device 420 determines whether there is any annotation data associated with that digital book and, if so, sends the annotation data to device 430.
Step 860 may also comprise storing date and/or time information that indicates when the annotation was created. This information may be displayed later when the annotation is consumed in the text context.
At step 862, device 410 displays text data associated with digital media item 402, which is a textual version of digital media item 404. Device 410 displays the text data of digital media item 402 based on a locally-stored copy of digital media item 402 or, if a locally-stored copy does not exist, may display the text data while the text data is streamed from intermediary device 420.
At step 864, device 410 determines when a portion of the textual version of the work (reflected in digital media item 402) that includes the text location (identified in step 860) is displayed. Alternatively, device 410 may display data that indicates that an annotation is available regardless of what portion of the textual version of the work, if any, is displayed.
At step 866, text media player 412 consumes the annotation data. If the annotation data is voice data, then consuming the annotation data may comprise playing the voice data or converting the voice data to text data and displaying the text data. If the annotation data is text data, then consuming the annotation data may comprises displaying the text data, for example, in a side panel of a GUI that displays a portion of the textual version of the work or in a new window that appears separate from the GUI.
Hardware OverviewAccording to one embodiment, the techniques described herein are implemented by one or more special-purpose computing devices. The special-purpose computing devices may be hard-wired to perform the techniques, or may include digital electronic devices such as one or more application-specific integrated circuits (ASICs) or field programmable gate arrays (FPGAs) that are persistently programmed to perform the techniques, or may include one or more general purpose hardware processors programmed to perform the techniques pursuant to program instructions in firmware, memory, other storage, or a combination. Such special-purpose computing devices may also combine custom hard-wired logic, ASICs, or FPGAs with custom programming to accomplish the techniques. The special-purpose computing devices may be desktop computer systems, portable computer systems, handheld devices, networking devices or any other device that incorporates hard-wired and/or program logic to implement the techniques.
For example,
Computer system 900 also includes a main memory 906, such as a random access memory (RAM) or other dynamic storage device, coupled to bus 902 for storing information and instructions to be executed by processor 904. Main memory 906 also may be used for storing temporary variables or other intermediate information during execution of instructions to be executed by processor 904. Such instructions, when stored in non-transitory storage media accessible to processor 904, render computer system 900 into a special-purpose machine that is customized to perform the operations specified in the instructions.
Computer system 900 further includes a read only memory (ROM) 908 or other static storage device coupled to bus 902 for storing static information and instructions for processor 904. A storage device 910, such as a magnetic disk or optical disk, is provided and coupled to bus 902 for storing information and instructions.
Computer system 900 may be coupled via bus 902 to a display 912, such as a cathode ray tube (CRT), for displaying information to a computer user. An input device 914, including alphanumeric and other keys, is coupled to bus 902 for communicating information and command selections to processor 904. Another type of user input device is cursor control 916, such as a mouse, a trackball, or cursor direction keys for communicating direction information and command selections to processor 904 and for controlling cursor movement on display 912. This input device typically has two degrees of freedom in two axes, a first axis (e.g., x) and a second axis (e.g., y), that allows the device to specify positions in a plane.
Computer system 900 may implement the techniques described herein using customized hard-wired logic, one or more ASICs or FPGAs, firmware and/or program logic which in combination with the computer system causes or programs computer system 900 to be a special-purpose machine. According to one embodiment, the techniques herein are performed by computer system 900 in response to processor 904 executing one or more sequences of one or more instructions contained in main memory 906. Such instructions may be read into main memory 906 from another storage medium, such as storage device 910. Execution of the sequences of instructions contained in main memory 906 causes processor 904 to perform the process steps described herein. In alternative embodiments, hard-wired circuitry may be used in place of or in combination with software instructions.
The term “storage media” as used herein refers to any non-transitory media that store data and/or instructions that cause a machine to operation in a specific fashion. Such storage media may comprise non-volatile media and/or volatile media. Non-volatile media includes, for example, optical or magnetic disks, such as storage device 910. Volatile media includes dynamic memory, such as main memory 906. Common forms of storage media include, for example, a floppy disk, a flexible disk, hard disk, solid state drive, magnetic tape, or any other magnetic data storage medium, a CD-ROM, any other optical data storage medium, any physical medium with patterns of holes, a RAM, a PROM, and EPROM, a FLASH-EPROM, NVRAM, any other memory chip or cartridge.
Storage media is distinct from but may be used in conjunction with transmission media. Transmission media participates in transferring information between storage media. For example, transmission media includes coaxial cables, copper wire and fiber optics, including the wires that comprise bus 902. Transmission media can also take the form of acoustic or light waves, such as those generated during radio-wave and infra-red data communications.
Various forms of media may be involved in carrying one or more sequences of one or more instructions to processor 904 for execution. For example, the instructions may initially be carried on a magnetic disk or solid state drive of a remote computer. The remote computer can load the instructions into its dynamic memory and send the instructions over a telephone line using a modem. A modem local to computer system 900 can receive the data on the telephone line and use an infra-red transmitter to convert the data to an infra-red signal. An infra-red detector can receive the data carried in the infra-red signal and appropriate circuitry can place the data on bus 902. Bus 902 carries the data to main memory 906, from which processor 904 retrieves and executes the instructions. The instructions received by main memory 906 may optionally be stored on storage device 910 either before or after execution by processor 904.
Computer system 900 also includes a communication interface 918 coupled to bus 902. Communication interface 918 provides a two-way data communication coupling to a network link 920 that is connected to a local network 922. For example, communication interface 918 may be an integrated services digital network (ISDN) card, cable modem, satellite modem, or a modem to provide a data communication connection to a corresponding type of telephone line. As another example, communication interface 918 may be a local area network (LAN) card to provide a data communication connection to a compatible LAN. Wireless links may also be implemented. In any such implementation, communication interface 918 sends and receives electrical, electromagnetic or optical signals that carry digital data streams representing various types of information.
Network link 920 typically provides data communication through one or more networks to other data devices. For example, network link 920 may provide a connection through local network 922 to a host computer 924 or to data equipment operated by an Internet Service Provider (ISP) 926. ISP 926 in turn provides data communication services through the world wide packet data communication network now commonly referred to as the “Internet” 928. Local network 922 and Internet 928 both use electrical, electromagnetic or optical signals that carry digital data streams. The signals through the various networks and the signals on network link 920 and through communication interface 918, which carry the digital data to and from computer system 900, are example forms of transmission media.
Computer system 900 can send messages and receive data, including program code, through the network(s), network link 920 and communication interface 918. In the Internet example, a server 930 might transmit a requested code for an application program through Internet 928, ISP 926, local network 922 and communication interface 918.
The received code may be executed by processor 904 as it is received, and/or stored in storage device 910, or other non-volatile storage for later execution.
In the foregoing specification, embodiments of the invention have been described with reference to numerous specific details that may vary from implementation to implementation. The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense. The sole and exclusive indicator of the scope of the invention, and what is intended by the applicants to be the scope of the invention, is the literal and equivalent scope of the set of claims that issue from this application, in the specific form in which such claims issue, including any subsequent correction.
Claims
1. A method comprising:
- receiving audio data that reflects an audible version of a work for which a textual version exists;
- performing a speech-to-text analysis of the audio data to generate text for portions of the audio data; and
- based on the text generated for the portions of the audio data, generating a mapping between a plurality of audio locations in the audio data and a corresponding plurality of text locations in the textual version of the work;
- wherein the method is performed by one or more computing devices.
2. The method of claim 1 wherein generating text for portions of the audio data includes generating text for portions of the audio data based, at least in part, on textual context of the work.
3. The method of claim 2, wherein generating text for portions of the audio data based, at least in part, on textual context of the work includes generating text based, at least in part, on one or more rules of grammar used in the textual version of the work.
4. The method of claim 2, wherein generating text for portions of the audio data based, at least in part, on textual context of the work includes limiting which words the portions can be translated to based on which words are in the textual version of the work, or a subset thereof.
5. The method of claim 4, wherein limiting which words the portions can be translated to based on which words are in the textual version of the work includes, for a given portion of the audio data, identifying a sub-section of the textual version of the work that corresponds to the given portion and limiting the words to only those words in the sub-section of the textual version of the work.
6. The method of claim 5, wherein:
- identifying the sub-section of the textual version of the work includes maintaining a current text location in the textual version of the work that corresponds to a current audio location, in the audio data, of the speech-to-text analysis; and
- the sub-section of the textual version of the work is a section associated with the current text location.
7. The method of claim 1, wherein the portions include portions that correspond to individual words, and the mapping maps the locations of the portions that correspond to individual words to individual words in the textual version of the work.
8. The method of claim 1, wherein the portions include portions that correspond to individual sentences, and the mapping maps the locations of the portions that correspond to individual sentences to individual sentences in the textual version of the work.
9. The method of claim 1, wherein the portions include portions that correspond to fixed amounts of data, and the mapping maps the locations of the portions that correspond to fixed amounts of data to corresponding locations in the textual version of the work.
10. The method of claim 1, wherein generating the mapping includes: (1) embedding anchors in the audio data; (2) embedding anchors in the textual version of the work; or (3) storing the mapping in a media overlay that is stored in association with the audio data or the textual version of the work.
11. The method of claim 1, wherein each of one or more text locations of the plurality of text locations indicates a relative location in the textual version of the work.
12. The method of claim 1, wherein one text location, of the plurality of text locations, indicates a relative location in the textual version of the work and another text location, of the plurality of text locations, indicates an absolute location from the relative location.
13. The method of claim 1, wherein each of one or more text locations of the plurality of text locations indicates an anchor within the textual version of the work.
14. A method comprising:
- receiving a textual version of a work;
- performing a text-to-speech analysis of the textual version to generate first audio data;
- based on the first audio data and the textual version, generating a first mapping between a first plurality of audio locations in the first audio data and a corresponding plurality of text locations in the textual version of the work;
- receiving second audio data that reflects an audible version of the work for which the textual version exists; and
- based on (1) a comparison of the first audio data and the second audio data and (2) the first mapping, generating a second mapping between a second plurality of audio locations in the second audio data and the plurality of text locations in the textual version of the work;
- wherein the method is performed by one or more computing devices.
15. A method comprising:
- receiving audio input;
- performing a speech-to-text analysis of the audio input to generate text for portions of the audio input;
- determining whether the text generated for portions of the audio input matches text that is currently displayed; and
- in response to determining that the text matches text that is currently displayed, causing the text that is currently displayed to be highlighted;
- wherein the method is performed by one or more computing devices.
16. One or more storage media storing instructions which, when executed by one or more processors, causes performance of the method recited in claim 1.
17. One or more storage media storing instructions which, when executed by one or more processors, causes performance of the method recited in claim 2.
18. One or more storage media storing instructions which, when executed by one or more processors, causes performance of the method recited in claim 3.
19. One or more storage media storing instructions which, when executed by one or more processors, causes performance of the method recited in claim 4.
20. One or more storage media storing instructions which, when executed by one or more processors, causes performance of the method recited in claim 5.
21. One or more storage media storing instructions which, when executed by one or more processors, causes performance of the method recited in claim 6.
22. One or more storage media storing instructions which, when executed by one or more processors, causes performance of the method recited in claim 7.
23. One or more storage media storing instructions which, when executed by one or more processors, causes performance of the method recited in claim 8.
24. One or more storage media storing instructions which, when executed by one or more processors, causes performance of the method recited in claim 9.
25. One or more storage media storing instructions which, when executed by one or more processors, causes performance of the method recited in claim 10.
26. One or more storage media storing instructions which, when executed by one or more processors, causes performance of the method recited in claim 11.
27. One or more storage media storing instructions which, when executed by one or more processors, causes performance of the method recited in claim 12.
28. One or more storage media storing instructions which, when executed by one or more processors, causes performance of the method recited in claim 13.
29. One or more storage media storing instructions which, when executed by one or more processors, causes performance of the method recited in claim 14.
30. One or more storage media storing instructions which, when executed by one or more processors, causes performance of the method recited in claim 15.
Type: Application
Filed: Oct 6, 2011
Publication Date: Dec 6, 2012
Applicant: APPLE INC. (Cupertino, CA)
Inventors: Xiang Cao (Sunnyvale, CA), Alan C. Cannistraro (San Francisco, CA), Gregory S. Robbin (Mountain View, CA), Casey M. Dougherty (San Francisco, CA)
Application Number: 13/267,738
International Classification: G10L 15/26 (20060101); G10L 13/08 (20060101);