Abstract: Techniques are provided for training of a text independent (TI) speaker recognition (SR) model. A methodology implementing the techniques according to an embodiment includes measuring context data associated with collected TI speech utterances from a user and identifying the user based on received identity measurements. The method further includes performing a speech quality analysis and a speaker state analysis based on the utterances, and evaluating a training merit value of the utterances, based on the speech quality analysis and the speaker state analysis. If the training merit value exceeds a threshold value, the utterances are stored as training data in a training database. The database is indexed by the user identity and the context data. The method further includes determining whether the stored training data has achieved a sufficiency level for enrollment of a TI SR model, and training the TI SR model for the identified user and context.

Abstract: Systems, methods, and devices for computer-generating responses and sending responses to communications when the recipient of the communication is unavailable are disclosed. An individual may send a message (either audio or text) to a recipient. The recipient may be unavailable to contemporaneously respond to the message (e.g., the recipient may be performing an action that makes is difficult or impractical for the recipient to contemporaneously respond to the audio message). When the recipient is unavailable, a response to the message is generated and sent without receiving an instruction from the recipient to do so. The response may be sent to the message originating individual, and content of the response may thereafter be sent to the recipient to receive feedback regarding the correctness of the response. Alternatively, the response content may first be sent to the recipient to receive the feedback, and thereafter the response may be sent to the message originating individual.

Abstract: A system is capable of automatically adjusting or reconstructing a baseline expression to generate a parallelized expression. Evaluation of the parallelized expression provide a substantially similar output as the evaluation of the baseline query in more efficient manner. In some implementations, data indicating an expression to be evaluated on a primary thread of the one or more processors is obtained. Elements of the expression are identified. The elements are grouped into a parse tree representation. Elements of the expression are classified as belonging to either a first category that includes elements that are eligible for parallel processing or a second category that includes elements that are not eligible for parallel processing. A particular element that is classified as belonging to the first category is identified and evaluated on a non-primary thread of the one or more processors. The non-primary thread is evaluated in parallel with the primary thread.

Abstract: A system and method for extracting a relevant phrase from text. The system and method may build a plurality of n-gram phrases using a seed from a seed list as a start, a middle, or an end of each n-gram phrase. The seed list may be directed to a specific vehicle system and each seed may indicate a symptom, part, or action to extract relevant phrases from vehicle information verbatims. The plurality of n-gram phrases may be filtered to obtain one or more relevant phrases. The filtering process may include calculating an external relevance factor, an internal relevance factor, or a context pattern relevance factor.

Abstract: A method of producing output indicative of the content of speech or mouthed speech from movement of speech articulators is described. The method may including fixing a plurality of magnets respectively to a plurality of speech articulators of a human individual. Providing a support. Providing a plurality of signal magnetic field sensors. Providing at least three reference magnetic field sensors orientated differently from one another with respect to the Earth's magnetic field. The signal and reference magnetic field sensors being fixed to the support which holds the sensors in fixed spatial relationships to one another. Producing, over a period of time, a respective signal from each signal magnetic field sensor and a respective signal from each reference magnetic field sensor. Obtaining, over the period of time, for each said signal magnetic field sensor signal, a respective correction value.

Abstract: Systems and methods are provided for analyzing voice-based audio inputs. A voice-based audio input associated with a user (e.g., wherein the voice-based audio input is a prompt or a command) is received and measures of one or more features are extracted. One or more parameters are calculated based on the measures of the one or more features. The occurrence of one or more mistriggers is identified by inputting the one or more parameters into a predictive model. Further, systems and methods are provided for identifying human mental health states using mobile device data. Mobile device data (including sensor data) associated with a mobile device corresponding to a user is received. Measurements are derived from the mobile device data and input into a predictive model. The predictive model is executed and outputs probability values of one or more symptoms associated with the user.

Abstract: A weighting function determination method includes obtaining a line spectral frequency (LSF) coefficient or an immitance spectral frequency (ISF) coefficient from a linear predictive coding (LPC) coefficient of an input signal and determining a weighting function by combining a first weighting function based on spectral analysis information and a second weighting function based on position information of the LSF coefficient or the ISF coefficient.

Abstract: Embodiments of the invention may be used to implement a rate converter that includes: 6 channels in forward (audio) path, each channel having a 24-bit signal path per channel, an End-to-end SNR of 110 dB, all within the 20 Hz to 20 KHz bandwidth. Embodiment may also be used to implement a rate converter having: 2 channels in a reverse path, such as for voice signals, 16-bit signal path per channel, an End-to-end SNR of 93 dB, all within 20 Hz to 20 KHz bandwidth. The rate converter may include sample rates such as 8, 11.025, 12, 16, 22.05, 24, 32 44.1, 48, and 96 KHz. Further, rate converters according to embodiments may include a gated clock in low-power mode to conserve power.

Abstract: A method for processing messages pertaining to an event includes receiving a plurality of messages pertaining to the event from electronic communication devices associated with a plurality of observers of the event, generating a first message stream that includes only a portion of the plurality of messages corresponding to a first participant in the event, identifying a first sub-event in the first message stream with reference to a time distribution of messages and content distribution of messages in the first message stream, generating a sub-event summary with reference to a portion of the plurality of messages in the first message stream that are associated with the first sub-event, and transmitting the sub-event summary to a plurality of electronic communication devices associated with a plurality of users who are not observers of the event.

Abstract: A home assistant device assisting with the setup and troubleshooting of devices is described. An assistant device can determine setup instructions for devices. The setup instructions for one device can be determined the technical aptitude of the user and assistant the user with setting up devices within their own technical abilities. The setup instructions can then be provided.

Abstract: A device includes a processor and a transmitter. The processor is configured to determine a first mismatch value indicative of a first amount of a temporal mismatch between a first audio signal and a second audio signal. The processor is also configured to determine a second mismatch value indicative of a second amount of a temporal mismatch between the first audio signal and the second audio signal. The processor is further configured to determine an effective mismatch value based on the first mismatch value and the second mismatch value. The processor is also configured to generate at least one encoded signal having a bit allocation. The bit allocation is at least partially based on the effective mismatch value. The transmitter configured to transmit the at least one encoded signal to a second device.

Abstract: A device includes a processor and a transmitter. The processor is configured to determine a first value and a second value indicative of a first amount and a second amount, respectively, of a temporal mismatch between a first audio signal and a second audio signal. The processor is also configured to determine an effective value based on the first value and the second value, to select, based on the effective value, a first coding mode and a second coding mode, and to generate at least one encoded signal having a bit allocation. The at least one encoded signal is based on a first encoded signal and a second encoded signal that are based on the first coding mode and the second coding mode, respectively. The bit allocation is at least partially based on the effective mismatch value. The transmitter is configured to transmit the at least one encoded signal.

Abstract: A dialog system for use in a multi-user, multi-domain environment. The dialog system understands user requests when multiple users are interacting with each other as well as the dialog system. The dialog system uses multi-human conversational context to improve domain detection. Using interactions between multiple users allows the dialog system to better interpret machine directed conversational inputs in multi-user conversational systems. The dialog system employs topic segmentation to chunk conversations for determining context boundaries. Using general topic segmentation methods, as well as the specific domain detector trained with conversational inputs collected by a single user system, allows the dialog system to better determine the relevant context. The use of conversational context helps reduce the domain detection error rate, especially in certain domains, and allows for better interactions with users when the machine addressed turns are not recognized or are ambiguous.

Abstract: A home assistant device assisting with the setup of devices is described. An assistant device can determine setup instructions for devices. The setup instructions for one device can be determined to include a step requesting information related to the setup of another device. The setup of the devices can be ordered based on that determination. The setup instructions can then be provided.

Abstract: Disambiguation in mention detection. The method includes: determining at least one location in a text at which a target surface form in the text appears; obtaining an overall word-bag context of the target surface form in the text, the word-bag context at each of the at least one location including words within a predetermined neighborhood of the location; obtaining an overall resource context of the target surface form in the text, the resource context at each of the at least one location including resources corresponding to a further surface form within a predetermined neighborhood of the location; and determining a similarity between the target surface form and a candidate resource for the target surface form based on the overall word-bag context and the overall resource context. A system for disambiguation in mention detection is also provided.

Abstract: Technology for improving the predictive accuracy of input word recognition on a device by dynamically updating the lexicon of recognized words based on the word choices made by similar users. The technology collects users' vocabulary choices (e.g., words that each user uses, or adds to or removes from a word recognition dictionary), associates users who make similar choices, aggregates related vocabulary choices, filters the words, and sends words identified as likely choices for that user to the user's device. Clusters may include, for example, users in a particular location (e.g., sets of people who use words such as “Puyallup,” “Gloucester,” or “Waiheke”), users with a particular professional or hobby vocabulary, or application-specific vocabulary (e.g., word choices in map searches or email messages).

Abstract: A method for ranking candidate speech recognition results includes generating, with a controller, a plurality of feature vectors for the candidate speech recognition results, each feature vector including one or more of trigger pair features, a confidence score feature, and word-level features. The method further includes providing the plurality of feature vectors as inputs to a neural network, generating a plurality of ranking scores corresponding to the plurality of feature vectors for the plurality of candidate speech recognition results based on an output layer of the neural network, and operating the automated system using the candidate speech recognition result in the plurality of candidate speech recognition results corresponding to a highest ranking score in the plurality of ranking scores as input.

Abstract: A voice output control device includes a control unit. The control unit controls a voice output device to output voice information items according to output requests transmitted from multiple output request units. The control unit compares a high and low relationship of information values preliminary set in the voice information items corresponding to the output requests, and controls the voice output device to output preferentially the voice information item having a higher information value. The control unit determines whether a display device outputs a content corresponding to each voice information item. The control unit sets each information value variably according to a determination result.

Abstract: A method for providing information to a user in response to a received user query. A natural language analysis generates substrings relevant to an input user query pertaining to a problem a user experiences with a product or service. An ontology analysis outputs: terms of an ontology matching the relevant generated substrings; and relationships between the terms. Elements of a perfect or complete query are captured and include information pertaining to the user's problem. The input user query is refined based on the outputted terms and relationships between the terms. A search query is performed, based on the refined user query. The results of the search are provided to the user.

Abstract: Network connected devices are controlled. A command is received. A graph model is applied to identify a subset of nodes related to the command. The graph model includes a plurality of nodes that each correspond to a device and the graph model includes a plurality of edges that specify relationships between the plurality of nodes. The subset of nodes is activated in response to the command.