Abstract: Systems, methods and apparatus for learning parsing rules and argument identification from crowdsourcing of proposed command inputs are disclosed. Crowdsourcing techniques are used to generate rules for parsing input sentences. A parse is used to determine whether the input sentence invokes a specific action, and if so, what arguments are to be passed to the invocation of the action.

Abstract: A language processing system identifies, from log data, command inputs that parsed to a parsing rule associated with an action. If the command input has a signal indicative of user satisfaction, where the signal is derived from data that is not generated from performance of the action (e.g., user interactions with data provided in response to the performance of another, different action; resources identified in response to the performance of another, different action having a high quality score; etc.), then exception data is generated for the parsing rule. The exception data specifies the particular instance of the sentence parsed by the parsing rule, and precludes invocation of the action associated with the rule.

Abstract: Methods and apparatus for audio watermarking a substantially silent media content presentation are disclosed. An example method to audio watermark a media content presentation disclosed herein comprises obtaining a watermarked noise signal comprising a watermark and a noise signal having energy substantially concentrated in an audible frequency band, the watermarked noise signal attenuated to be substantially inaudible without combining with a separate audio signal, associating the watermarked noise signal with a substantially silent content component of the media content presentation, the media content presentation comprising one or more media content components, and outputting the watermarked noise signal during presentation of the substantially silent content component.

Abstract: In speech processing systems, compensation is made for sudden changes in the background noise in the average signal-to-noise ratio (SNR) calculation. SNR outlier filtering may be used, alone or in conjunction with weighting the average SNR. Adaptive weights may be applied on the SNRs per band before computing the average SNR. The weighting function can be a function of noise level, noise type, and/or instantaneous SNR value. Another weighting mechanism applies a null filtering or outlier filtering which sets the weight in a particular band to be zero. This particular band may be characterized as the one that exhibits an SNR that is several times higher than the SNRs in other bands.

Abstract: A computer implemented method for performing sign language translation based on movements of a user is provided. A capture device detects motions defining gestures and detected gestures are matched to signs. Successive signs are detected and compared to a grammar library to determine whether the signs assigned to gestures make sense relative to each other and to a grammar context. Each sign may be compared to previous and successive signs to determine whether the signs make sense relative to each other. The signs may further be compared to user demographic information and a contextual database to verify the accuracy of the translation. An output of the match between the movements and the sign is provided.

Abstract: Methods and systems are provided for generating automatic program recommendations based on user interactions. In some embodiments, control circuitry processes verbal data received during an interaction between a user of a user device and a person with whom the user is interacting. The control circuitry analyzes the verbal data to automatically identify a media asset referred to during the interaction by at least one of the user and the person with whom the user is interacting. The control circuitry adds the identified media asset to a list of media assets associated with the user of the user device. The list of media assets is transmitted to a second user device of the user.

Abstract: A method, a computer readable medium and a system for tagging automatic speech recognition that comprises, collecting an utterance, analyzing the utterance, and assigning a tag to the analyzed utterance.

Abstract: Techniques disclosed herein include systems and methods for privacy-sensitive training data collection for updating acoustic models of speech recognition systems. In one embodiment, the system locally creates adaptation data from raw audio data. Such adaptation can include derived statistics and/or acoustic model update parameters. The derived statistics and/or updated acoustic model data can then be sent to a speech recognition server or third-party entity. Since the audio data and transcriptions are already processed, the statistics or acoustic model data is devoid of any information that could be human-readable or machine readable such as to enable reconstruction of audio data. Thus, such converted data sent to a server does not include personal or confidential information. Third-party servers can then continually update speech models without storing personal and confidential utterances of users.

Abstract: Disclosed herein are systems, computer-implemented methods, and computer-readable media for recognizing speech. The method includes receiving speech from a user, perceiving at least one speech dialect in the received speech, selecting at least one grammar from a plurality of optimized dialect grammars based on at least one score associated with the perceived speech dialect and the perceived at least one speech dialect, and recognizing the received speech with the selected at least one grammar. Selecting at least one grammar can be further based on a user profile. Multiple grammars can be blended. Predefined parameters can include pronunciation differences, vocabulary, and sentence structure. Optimized dialect grammars can be domain specific. The method can further include recognizing initial received speech with a generic grammar until an optimized dialect grammar is selected. Selecting at least one grammar from a plurality of optimized dialect grammars can be based on a certainty threshold.

Abstract: An apparatus for processing an audio signal and method thereof are disclosed. The present invention includes receiving, by an audio processing apparatus, an audio signal including a first data of a first block encoded with rectangular coding scheme and a second data of a second block encoded with non-rectangular coding scheme; receiving a compensation signal corresponding to the second block; estimating a prediction of an aliasing part using the first data; and, obtaining a reconstructed signal for the second block based on the second data, the compensation signal and the prediction of aliasing part.

Abstract: A system for detecting related topics and competition topics for a target topic includes an information extracting apparatus configured to create topic templates and association words from documents created online to generate topic templates and association words. The system also includes a related topic detecting apparatus configured to detect and trace related topics and competition topics for the target topic based on the topic templates and the association words.

Abstract: Techniques are described for selecting audio from locations that are most likely to be sources of spoken commands or words. Directional audio signals are generated to emphasize sounds from different regions of an environment. The directional audio signals are processed by an automated speech recognizer to generate recognition confidence values corresponding to each of the different regions, and the region resulting in the highest recognition confidence value is selected as the region most likely to contain a user who is speaking commands.

Abstract: Features are disclosed for processing a user utterance with respect to multiple subject matters or domains, and for selecting a likely result from a particular domain with which to respond to the utterance or otherwise take action. A user utterance may be transcribed by an automatic speech recognition (“ASR”) module, and the results may be provided to a multi-domain natural language understanding (“NLU”) engine. The multi-domain NLU engine may process the transcription(s) in multiple individual domains rather than in a single domain. In some cases, the transcription(s) may be processed in multiple individual domains in parallel or substantially simultaneously. In addition, hints may be generated based on previous user interactions and other data. The ASR module, multi-domain NLU engine, and other components of a spoken language processing system may use the hints to more efficiently process input or more accurately generate output.

Abstract: An apparatus for processing an audio signal and method thereof are disclosed. The present invention includes receiving, by an audio processing apparatus, an audio signal including a first data of a first block encoded with rectangular coding scheme and a second data of a second block encoded with non-rectangular coding scheme; receiving a compensation signal corresponding to the second block; estimating a prediction of an aliasing part using the first data; and, obtaining a reconstructed signal for the second block based on the second data, the compensation signal and the prediction of aliasing part.

Abstract: Method and apparatus for audio intelligibility enhancement and computing apparatus are provided. The method includes the following steps. Environment noise is detected by performing voice activity detection according to a detected audio signal from at least a microphone of a computing device. Noise information is obtained according to the detected environment noise and a first audio signal. A second audio signal is outputted by boosting the first audio signal under an adjustable headroom by the computing device according to the noise information and the first audio signal.

Abstract: A natural language system may receive user-input. The user-input may include personal or restrictable information. The natural language system may provide a dual processing system. The natural language system may store a true copy of the user-input, which may include the personal or restrictable information. The natural language system may also generate an obfuscated copy of the user-input that does not contain personal or restricted information. The true copy of the user-input may be stored in a secure storage system and may be retrieved by authorized personnel, which may include the user who provided the user-input. The obfuscated copy of the user-input may be stored in a storage system and may be employed in ongoing training of the natural language system.

Abstract: Methods and computer systems for translating sentences between languages from an intermediate language-independent semantic representation are provided. Based on a comprehensive understanding about languages and semantics, exhaustive linguistic descriptions are used to analyze sentences, build syntactic structures and language independent semantic structures and representations, and synthesize one or more sentences in a natural or artificial language. A computer system is also provided to analyze and synthesize various linguistic structures and perform translation of a wide spectrum of various sentence types. As result, a generalized data structure, such as a semantic structure, is generated from a sentence of an input language and can be transformed into a natural sentence expressing its meaning correctly in an output language. The methods and systems can be applied to automated abstracting, machine translation, natural language processing, control systems, Internet information retrieval, etc.

Abstract: Devices, systems, methods, media, and programs for detecting an emotional state change in an audio signal are provided. A plurality of segments of the audio signal is received, with the plurality of segments being sequential. Each segment of the plurality of segments is analyzed, and, for each segment, an emotional state and a confidence score of the emotional state are determined. The emotional state and the confidence score of each segment are sequentially analyzed, and a current emotional state of the audio signal is tracked throughout each of the plurality of segments. For each segment, it is determined whether the current emotional state of the audio signal changes to another emotional state based on the emotional state and the confidence score of the segment.

Abstract: Techniques for transitioning an electronic device between device states. In one example, a voice-controlled device is configured to transition from a sleep state to an awake state in response to identifying a user speaking a predefined utterance. The techniques may determine whether the user has spoken the predefined utterance with reference to traditional speech-recognition techniques, as well as with reference to changes in the volume of a user's voice.

Abstract: An audio codec supporting both, time-domain and frequency-domain coding modes, having low-delay and an increased coding efficiency in terms of iterate/distortion ratio, is obtained by configuring the audio encoder such that same operates in different operating modes such that if the active operative mode is a first operating mode, a mode dependent set of available frame coding modes is disjoined to a first subset of time-domain coding modes, and overlaps with a second subset of frequency-domain coding modes, whereas if the active operating mode is a second operating mode, the mode dependent set of available frame coding modes overlaps with both subsets, i.e. the subset of time-domain coding modes as well as the subset of frequency-domain coding modes.