Abstract: A method for context-aware query recognition in an electronic device includes receiving user speech from an input device. A speech signal is generated from the user speech. It is determined if the speech signal includes an action to be performed and if the electronic device is the intended recipient of the user speech. If the recognized speech signal include the action and the intended recipient of the user speech is the electronic device, a command is generated for the electronic device to perform the action.

Abstract: A machine has a processor and a memory connected to the processor. The memory stores instructions executed by the processor to supply a name page in response to a request from an administrator machine. Name page updates are received from the administrator machine. The name page updates include participants and associated network contact information for the participants. A code is utilized to form a link to the name page. Prompts for textual name information and audio name information are supplied to a client machine that activates the link to the name page. Textual name information and audio name information are received from the client machine. The textual name information and audio name information are stored in association with the name page. Navigation tools are supplied to facilitate access to the textual name information and audio name information.

Abstract: A computer-implemented technique can include receiving a selection by a user of a single word in a document in a source language, the document being displayed in a viewing application executing at the computing device, obtaining contextual information from the document that is indicative of a context of the selected word, providing the selected word and its contextual information from the viewing application to a different translation application, obtaining potential translated words using the translation application, the selected word, and its contextual information, each potential translated word being a potential translation of the selected word to a different target language that is preferred by the user, and displaying the potential translated words.

Abstract: Methods are presented for generating a natural language model. The method may comprise: ingesting training data representative of documents to be analyzed by the natural language model, generating a hierarchical data structure comprising at least two topical nodes within which the training data is to be subdivided into by the natural language model, selecting a plurality of documents among the training data to be annotated, generating an annotation prompt for each document configured to elicit an annotation about said document indicating which node among the at least two topical nodes said document is to be classified into, receiving the annotation based on the annotation prompt; and generating the natural language model using an adaptive machine learning process configured to determine patterns among the annotations for how the documents in the training data are to be subdivided according to the at least two topical nodes of the hierarchical data structure.

Abstract: Embodiments of the disclosure generally relate to a dialog system allowing for automatically reactivating a speech acquiring mode after the dialog system delivers a response to a user request. The reactivation parameters, such as a delay, depend on a number of predetermined factors and conversation scenarios. The embodiments further provide for a method of operating of the dialog system. An exemplary method comprises the steps of: activating a speech acquiring mode, receiving a first input of a user, deactivating the speech acquiring mode, obtaining a first response associated with the first input, delivering the first response to the user, determining that a conversation mode is activated, and, based on the determination, automatically re-activating the speech acquiring mode within a first predetermined time period after delivery of the first response to the user.

Abstract: The present document relates to the determination of a 200 bitrate related to an encoded bitstream, and describes a method for determining an estimate of a bitrate of a bitstream comprising a sequence of frames comprising a varying number of bitsand corresponding to excerpts of an audio and/or video signal. At least two frames of the sequence of frames comprise a parameter indicative of a processing delay for the corresponding frame. The method comprises determining: a total number of bits for a subsequence of frames from the bitstream; a corrected number 201 of frames based on a number of frames comprised within the subsequence and the parameters of at least two frames of the subsequence; and a lower bitrate bound and an upper bitrate bound of the bitrate based on the total number of bits, the corrected number of frames and a frame rate of the bitstream.

Abstract: A voice control method and a voice control system are provided. The voice control method is adapted to a voice control apparatus connected to a local area network. The voice control method includes following steps. Voice data is received. A voice recognition is executed for the voice data to obtain voice print information and a prompt command corresponding to the voice data. Permission information corresponding to the voice print information is determined according to the voice print information and the prompt command. At least one electronic apparatus is controlled through the local area network according to at least one of the permission information, the prompt command and environment information.

Abstract: In an embodiment receiving input data over a computer network. The method also includes automatically generating topic-based metadata of the input data in relation to a multi-level taxonomy. The method also includes automatically determining parts of speech of tokens of the input data. The method also includes searching a metadata store using the tokens and the parts of speech, the searching including identifying, at a first level and a second level of the multi-level taxonomy, nodes that include metadata which sufficiently match the tokens and the parts of speech of the tokens, where the searching yields best-match grammar-based metadata. The method of also includes revising the best-match grammar-based metadata based at least in part on the automatically generated topic-based metadata.

Abstract: Techniques for creating groups of devices for controlling these groups with voice commands are described herein. For instance, an environment may include an array of secondary devices (or “smart appliances”, or simply “devices”) that are configured to perform an array of operations. Users may request to create different groups of these devices, such that the users may control entire groups at a single time with individual voice commands.

Abstract: Methods and systems for recognizing textual identifiers within a plurality of words are described. A textual representation of a voice input is received from a user. The textual representation includes a plurality of words. A keyword is identified in the textual representation. It is determined whether one or more words adjacent to the keyword correspond to a textual identifier of a collection of textual identifiers. Responsive to a determination that the one or more adjacent words correspond to a textual identifier, the keyword and the one or more adjacent words are replaced with the textual identifier.

Abstract: Embodiments are described for harmonicity estimation, audio classification, pitch determination and noise estimation. Measuring harmonicity of an audio signal includes calculation a log amplitude spectrum of audio signal. A first spectrum is derived by calculating each component of the first spectrum as a sum of components of the log amplitude spectrum on frequencies. In linear frequency scale, the frequencies are odd multiples of the component's frequency of the first spectrum. A second spectrum is derived by calculating each component of the second spectrum as a sum of components of the log amplitude spectrum on frequencies. In linear frequency scale, the frequencies are even multiples of the component's frequency of the second spectrum. A difference spectrum is derived subtracting the first spectrum from the second spectrum. A measure of harmonicity is generated as a monotonically increasing function of the maximum component of the difference spectrum within predetermined frequency range.

Abstract: Method and apparatus for reducing a size of databases required for recorded speech data.

Abstract: Embodiments of the present invention provide an approach for estimating the accuracy of a transcription of a voice recording. Specifically, in a typical embodiment, each word of a transcription of a voice recording is checked against a customer-specific dictionary and/or a common language dictionary. The number of words not found in either dictionary is determined. An accuracy number for the transcription is calculated from the number of said words not found and the total number of words in the transcription.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for automatic speech recognition using multi-dimensional models. In some implementations, audio data that describes an utterance is received. A transcription for the utterance is determined using an acoustic model that includes a neural network having first memory blocks for time information and second memory blocks for frequency information. The transcription for the utterance is provided as output of an automated speech recognizer.

Abstract: Techniques for defining a set of predefined device capabilities generally offered by available voice-controllable devices are described herein. Thereafter, as a particular user introduces new secondary devices into his environment and registers these devices, the techniques may identify the capabilities of the new device and map these capabilities to one or more of the predefined device capabilities of the set.

Abstract: The disclosure generally describes computer-implemented methods, software, and systems for self-learning localization services. A computer-implemented method includes: identifying, at a location remote from a first application, a request for localization of a string value associated with the first application from a source language to a target language, sending the string value to a translation request buffer in response to a determination that the localization of the string value in the target language is unavailable, and triggering, in response to satisfaction of at least one heuristic analysis, a translation process of the string value from the source language into the target language where the string value is retrieved from the translation request buffer. In some instances, the location remove from the first application is a centralized localization service accessible by remote requests from a plurality of applications.

Abstract: A “Facet Recommender” creates conversational recommendations for facets of particular conversational topics, and optionally for things associated with those facets, from consumer reviews or other social media content. The Facet Recommender applies a machine-learned facet model and optional sentiment-model, to identify facets associated with spans or segments of the content and to determine neutral, positive, or negative consumer sentiment associated with those facets and, optionally, things associated with those facets. These facets are selected by the facet model from a list or set of manually defined or machine-learned facets for particular conversational topic types. The Facet Recommender then generates new conversational utterances (i.e., short neutral, positive or negative suggestions) about particular facets based on the sentiments associated with those facets. In various implementations, utterances are fit to one or more predefined conversational frameworks.

Abstract: A computerized method for generating and evaluating natural language-generated text involves receiving, in a computer, data input by a user, generating, using a natural language generation technique, multiple instances of text stories based upon both contents of a corpus and the received data; analyzing the multiple instances of text stories as a weighted combination of computed geographic scores, distance scores, information content scores, replacement scores and extra aspect scores, providing a ranked set of the generated text stories to a user, receiving a selection of one of the text stories in the ranked set, and storing the selected story.

Abstract: A method and apparatus for speech recognition are provided. The method and the apparatus calculate signal to noise ratios (SNRs) of speech signals from a user received at speech recognition apparatuses. The method and the apparatus recognize a reference speech signal having a maximum SNR among the SNRs.

Abstract: A computer-implemented technique includes receiving, at a computing device including one or more processors, a user input (i) identifying a portion of a media stream being output from the computing device and (ii) indicating a request to translate the portion of the media stream from a source language to a target language. The technique includes transmitting, from the computing device, the portion of the media stream to a translation server via a network in response to receiving the user input. The technique includes receiving, at the computing device, a translated portion of the media stream from the translation server via the network, the translated portion of the media stream having been translated from the source language to the target language by the translation server. The technique also includes outputting, at the computing device, the translated portion of the media stream.