Abstract: A method for predicting a speech recognition quality of a phrase comprising at least one word includes: receiving, on a computer system including a processor and memory storing instructions, the phrase; computing, on the computer system, a set of features comprising one or more features corresponding to the phrase; providing the phrase to a prediction model on the computer system and receiving a predicted recognition quality value based on the set of features; and returning the predicted recognition quality value.

Abstract: A method for recognizing a voice includes receiving, as an input, a voice involving multiple languages, recognizing a first voice of the voice by using a voice recognition algorithm matched to a preset primary language, identifying the preset primary language and a non-primary language different from the preset primary language, which are included in the multiple languages, determining a type of the non-primary language based on context information, recognizing a second voice of the voice in the non-primary language by applying a voice recognition algorithm, which is matched to the non-primary language of the determined type, to the second voice, and outputting a result of recognizing the voice which is based on a result of recognizing the first voice and a result of recognizing the second voice.

Abstract: A method for receiving processed information at a remote device is described. The method includes transmitting from the remote device a verbal request to a first information provider and receiving a digital message from the first information provider in response to the transmitted verbal request. The digital message includes a symbolic representation indicator associated with a symbolic representation of the verbal request and data used to control an application. The method also includes transmitting, using the application, the symbolic representation indicator to a second information provider for generating results to be displayed on the remote device.

Abstract: A system for annotating words of a data corpus based upon their particular concept and their corresponding grammatical sense with Conceptual Numerical Identifiers (CNIs) from a Conceptual Dictionary, pairing the words based on conceptual inter-relating network (CIRN) rules, and determining if a selected plurality of paired words are grammatically, syntactically, and linguistically correct by matching CNIs from each pair of words.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving audio data encoding an utterance and environmental data, obtaining a transcription of the utterance, identifying an entity using the environmental data, submitting a query to a natural language query processing engine, wherein the query includes at least a portion of the transcription and data that identifies the entity, and obtaining one or more results of the query.

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: Differentiation testing is used to determine the usefulness of a term on a single-term basis or within a set of terms. Differentiation testing is performed by comparing an input against other input or a comparison set.

Abstract: Methods and system are provided for managing speech processing in an environment having at least two speech enabled systems. In one embodiment, a method includes: recording first user data that indicates an action of a user; determining, by a processor, a selection of a first speech enabled system based on the recorded user data; and generating, by the processor, a signal to at least one of activate and deactivate speech processing based on the first speech enabled system.

Abstract: A method, medium, and apparatus encoding and/or decoding a multichannel audio signal. The method includes detecting the type of spatial extension data included in an encoding result of an audio signal, if the spatial extension data is data indicating a core audio object type related to a technique of encoding core audio data, detecting the core audio object type; decoding core audio data by using a decoding technique according to the detected core audio object type, if the spatial extension data is residual coding data, decoding the residual coding data by using the decoding technique according to the core audio object type, and up-mixing the decoded core audio data by using the decoded residual coding data. According to the method, the core audio data and residual coding data may be decoded by using an identical decoding technique, thereby reducing complexity at the decoding end.

Abstract: A vehicle based system and method for receiving voice inputs and determining whether to perform a voice recognition analysis using in-vehicle resources or resources external to the vehicle.

Abstract: Techniques are described for a real-time visualization of data in an integrated authoring environment. In one example, a method includes receiving text information. The method also includes comparing the dynamically entered text information against a data source, wherein the comparing comprises applying natural language processing (NLP) to determine one or more assertion statements in the text information that references data from the data source. The method also includes retrieving the referenced data associated with the one or more assertion statements from the data source. The method further includes generating a visual representation of the referenced data associated with the one or more assertion statements. The method also includes displaying the visual representation, wherein the visual representation is integrated with an authoring interface.

Abstract: A voice dialogue method performed by a voice dialog system includes: a voice signal generation unit; a voice dialog agent unit; a voice output unit; and a voice input control unit, the method including: a step of, by the voice signal generation unit, receiving a voice input and generating a voice signal based on the received voice input; a step of, by the voice dialog agent unit, performing voice recognition processing on the voice signal and performing processing based on a result of the voice recognition processing to generate a response signal; a step of, by the voice output unit, outputting a voice based on the response signal; and a step of, when the voice output unit outputs the voice, by the voice input control unit, keeping the voice signal generation unit, for predetermined period after output of the voice, a receivable state in which a voice input is receivable.

Abstract: A terminology marker system integrates a terminology analytical component for quantifying the amount of linguistic noise found in the translation output as measured against a dictionary; further, correlating the noise measured on a continuous basis enables the analytical component to build terminology predictive models used in a feedback loop to upstream components of the supply chain to improve future translation of new content. The system also provides a smart terminology assessment component for assessing linguistic assets and improving the quality of those assets to assist in translation. The system also provides a smart terminology evaluation component that is able to analyze MT output to make smart decisions on reducing the amount of post editing corrections needed for delivering a persistent level of translation quality.

Abstract: An electronic device includes a processor and a memory coupled to the processor. The memory stores instructions that, when executed by the processor, cause the processor to perform operations including determining whether a text prompt received from a wireless device corresponds to first synthesized speech data stored at the memory. The operations include, in response to a determination that the text prompt does not correspond to the first synthesized speech data, determining whether a network is accessible. The operations include, in response to a determination that the network is accessible, sending a text-to-speech (TTS) conversion request to a server via the network. The operation further include, in response to receiving second synthesized speech data from the server, storing the second synthesized speech data at the memory.

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: Conversational interactions between humans and computer systems can be provided by a computer system that classifies an input by conversation type, and provides human authored responses for conversation types. The input classification can be performed using trained binary classifiers. Training can be performed by labeling inputs as either positive or negative examples of a conversation type. Conversational responses can be authored by the same individuals that label the inputs used in training the classifiers. In some cases, the process of training classifiers can result in a suggestion of a new conversation type, for which human authors can label inputs for a new classifier and write content for responses for that new conversation type.

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: 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: Disclosed herein are systems, methods, and computer readable-media for answering a communication notification. The method for answering a communication notification comprises receiving a notification of communication from a user, converting information related to the notification to speech, outputting the information as speech to the user, and receiving from the user an instruction to accept or ignore the incoming communication associated with the notification. In one embodiment, information related to the notification comprises one or more of a telephone number, an area code, a geographic origin of the request, caller id, a voice message, address book information, a text message, an email, a subject line, an importance level, a photograph, a video clip, metadata, an IP address, or a domain name. Another embodiment involves notification assigned an importance level and repeat attempts at notification if it is of high importance.

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.