Abstract: Disclosed is an audio signal processing method comprising the steps of: receiving an audio signal containing current frame data; generating a first temporary output signal for the current frame when an error occurs in the current frame data, by carrying out frame error concealment with respect to the current frame data a random codebook; generating a parameter by carrying out one or more of short-term prediction, long-term prediction and a fixed codebook search based on the first temporary output signal; and memory updating the parameter for the next frame; wherein the parameter comprises one or more of pitch gain, pitch delay, fixed codebook gain and a fixed codebook.

Abstract: The voice recognition device according to the present disclosure includes a communication interface that communicates with an external device, a first microphone that collects sound to produce audio data, and a controller that analyzes the audio data produced by the first microphone, determines contents of a designation corresponding to an analysis result, and then controls its own device based on a determination result, and yet controls its own device to urge a user to use the external device when the contents of the designation corresponding to the analysis result cannot be determined.

Abstract: A system and method that improves obtaining similarity measure between concepts based on Latent Semantic Analysis by taking onto account graph structure derived from the knowledge bases by using a vector propagation algorithm, in the context domain, such as a medical domain. Concepts contained in a corpus of documents are expressed in a graph wherein each node is a concept and edges between node express relation between concepts weighted by the number of semantic relations determined from the corpus. A vector of neighbors is created and assigned to each concept, thereby providing an improved similarity measure between documents, i.e., corpus and query against corpus.

Abstract: A method, device and system for providing a language service are disclosed. In some embodiments, the method is performed at a computer system having one or more processors and memory for storing programs to be executed by the one or more processors. The method includes receiving a first message from a client device. The method includes determining if the first message is in a first language or a second language different than the first language. The method includes translating the first message into a second message in the second language if the first message is in the first language. The method includes, alternatively, generating a third message in the second language if the first message is in the second language, where the third message includes a conversational response to the first message. The method further includes returning one of the second message and the third message to the client device.

Abstract: Example embodiments of the present invention may include a method that provides transcribing spoken utterances occurring during a call and assigning each of the spoken utterances with a corresponding set of first classifications. The method may also include determining a confidence rating associated with each of the spoken utterances and the assigned set of first classifications, and performing at least one of reclassifying the spoken utterances with new classifications based on at least one additional classification operation, and adding the assigned first classifications and the corresponding plurality of spoken utterances to a training data set.

Abstract: A method for testing the display of bi-directional language script prior to translation in an application under test can include using unidirectional glyphs with shaping indicators to simulate right-to-left characters. The using step can include reversing an ordering of a first set of unidirectional text characters in an input string and mapping the unidirectional text characters to right-to-left code points in a bi-directional language code page to produce a pseudo-translated string. Multiple unidirectional language glyphs can be loaded where each corresponds to a same one of the right-to-left character code points as had been used to produce the pseudo-translation. The pseudo-translation and the glyphs can be combined to simulate right-to-left character rendering in the application under test such the resultant output is visually similar to the input string. Finally, the glyphs can include character shaping indicia such that a resultant output allows for the detection of shaping errors.

Abstract: Creating and processing a natural language grammar set of data based on an input text string are disclosed. The method may include tagging the input text string, and examining, via a processor, the input text string for at least one first set of substitutions based on content of the input text string. The method may also include determining whether the input text string is a substring of a previously tagged input text string by comparing the input text string to a previously tagged input text string, such that the substring determination operation determines whether the input text string is wholly included in the previously tagged input text string.

Abstract: Some aspects include transforming data, at least a portion of which has been processed to determine at least one representative vector associated with each of a plurality of classifications associated with the data to obtain a plurality of representative vectors. Techniques comprise determining a first transformation based, at least in part, on the plurality of representative vectors, applying at least the first transformation to the data to obtain transformed data, and fitting a plurality of clusters to the transformed data to obtain a plurality of established clusters. Some aspects include classifying input data by transforming the input data using at least the first transformation and comparing the transformed input data to the established clusters.

Abstract: Improved audio classification is provided for encoding applications. An initial classification is performed, followed by a finer classification, to produce speech classifications and music classifications with higher accuracy and less complexity than previously available. Audio is classified as speech or music on a frame by frame basis. If the frame is classified as music by the initial classification, that frame undergoes a second, finer classification to confirm that the frame is music and not speech (e.g., speech that is tonal and/or structured that may not have been classified as speech by the initial classification). Depending on the implementation, one or more parameters may be used in the finer classification. Example parameters include voicing, modified correlation, signal activity, and long term pitch gain.

Abstract: In a method for the operator control of a motor vehicle having a display for displaying variable information and having a microphone, the viewing direction of an operator of the motor vehicle is ascertained, it is checked whether the viewing direction of the operator is aimed toward the display, and information assigned to an acoustic command is shown on the display when a corresponding acoustic command is given while the viewing direction of the operator is aimed toward the display.

Abstract: Topics of potential interest to a user, useful for purposes such as targeted advertising and product recommendations, can be extracted from voice content produced by a user. A computing device can capture voice content, such as when a user speaks into or near the device. One or more sniffer algorithms or processes can attempt to identify trigger words in the voice content, which can indicate a level of interest of the user. For each identified potential trigger word, the device can capture adjacent audio that can be analyzed, on the device or remotely, to attempt to determine one or more keywords associated with that trigger word. The identified keywords can be stored and/or transmitted to an appropriate location accessible to entities such as advertisers or content providers who can use the keywords to attempt to select or customize content that is likely relevant to the user.

Abstract: An adaptive equalization system that adjusts the spectral shape of a speech signal based on an intelligibility measurement of the speech signal may improve the intelligibility of the output speech signal. Such an adaptive equalization system may include a speech intelligibility measurement module, a spectral shape adjustment module, and an adaptive equalization module. The speech intelligibility measurement module is configured to calculate a speech intelligibility measurement of a speech signal. The spectral shape adjustment module is configured to generate a weighted long-term speech curve based on a first predetermined long-term average speech curve, a second predetermined long-term average speech curve, and the speech intelligibility measurement. The adaptive equalization module is configured to adapt equalization coefficients for the speech signal based on the weighted long-term speech curve.

Abstract: Techniques for determining when to perform an action associated with a voice command and when to disregard the voice command. In some instances, the techniques reference an identity of a user that utters a command when making this determination. For instance, if a first user awakens a device or initially begins providing voice commands to the device, the device or another computing device may perform actions associated with subsequent voice commands uttered by the same user, while disregarding voice commands from other users. That is, because the device is engaging in a dialog with a first user, the device may refrain from engaging in a dialog with a different user. Additionally or alternatively, the device may begin a new dialog with the different user, either upon identifying the command of the other user or upon finishing the dialog with the first user.

Abstract: Processes capable of accepting linguistic input in one or more languages are generated by re-using existing linguistic components associated with a different anchor language, together with machine translation components that translate between the anchor language and the one or more languages. Linguistic input is directed to machine translation components that translate such input from its language into the anchor language. Those existing linguistic components are then utilized to initiate responsive processing and generate output. Optionally, the output is directed through the machine translation components. A language identifier can initially receive linguistic input and identify the language within which such linguistic input is provided to select an appropriate machine translation component.

Abstract: The subject matter of this specification can be implemented in, among other things, a computer-implemented method for correcting words in transcribed text including receiving speech audio data from a microphone. The method further includes sending the speech audio data to a transcription system. The method further includes receiving a word lattice transcribed from the speech audio data by the transcription system. The method further includes presenting one or more transcribed words from the word lattice. The method further includes receiving a user selection of at least one of the presented transcribed words. The method further includes presenting one or more alternate words from the word lattice for the selected transcribed word. The method further includes receiving a user selection of at least one of the alternate words. The method further includes replacing the selected transcribed word in the presented transcribed words with the selected alternate word.

Abstract: A post is generated that identifies different types of activity in a computer system, such as changes to the data in the computer system. The post is generated in a language-neutral way. An activity feed generator generates a language-specific post and distributes it, in an activity feed, to a set of users, based on user preferences. The activity feed generator can also access a security model so that only users with sufficient privileges receive the post in their activity feed.

Abstract: Methods and systems for providing translation assistance are disclosed. A method includes: storing translation data representing changes to translations during a time interval between a first time and a second time; building the source code project into a reference application in the second language, comprising: replacing an identifier of each text message in the source code project with a translation of the text message in the second language made at the second time, and for a text message whose translation has changed during the time interval, inserting the identifier of the text message whose translation has changed as hidden information associated with the translation of the text message; and rendering the reference application for presentation to a user for translation checking, including highlighting the text messages that have an associated hidden identifier.

Abstract: A method and system of speech synthesis. A text input is received in a text-to-speech system and, using a processor of the system, the text input is processed into synthesized speech which is established as unintelligible. The text input is reprocessed into subsequent synthesized speech and output to a user via a loudspeaker to correct the unintelligible synthesized speech. In one embodiment, the synthesized speech can be established as unintelligible by predicting intelligibility of the synthesized speech, and determining that the predicted intelligibility is lower than a minimum threshold. In another embodiment, the synthesized speech can be established as unintelligible by outputting the synthesized speech to the user via the loudspeaker, and receiving an indication from the user that the synthesized speech is not intelligible.

Abstract: A system, method and computer readable medium that provides an automated web transcription service is disclosed. The method may include receiving input speech from a user using a communications network, recognizing the received input speech, understanding the recognized speech, transcribing the understood speech to text, storing the transcribed text in a database, receiving a request via a web page to display the transcribed text, retrieving transcribed text from the database, and displaying the transcribed text to the requester using the web page.

Abstract: Audio content is converted to text using speech recognition software. The text is then associated with a distinct voice or a generic placeholder label if no distinction can be made. From the text and voice information, a word cloud is generated based on key words and key speakers. A visualization of the cloud displays as it is being created. Words grow in size in relation to their dominance. When it is determined that the predominant words or speakers have changed, the word cloud is complete. That word cloud continues to be displayed statically and a new word cloud display begins based upon a new set of predominant words or a new predominant speaker or set of speakers. This process may continue until the meeting is concluded. At the end of the meeting, the completed visualization may be saved to a storage device, sent to selected individuals, removed, or any combination of the preceding.