Abstract: A voice recognition processing apparatus includes a voice acquirer, a first voice recognizer, a second voice recognizer, a sorter, a storage device, and a processor. The voice acquirer acquires a voice uttered by a user and outputs voice information. The first voice recognizer converts the voice information into first information. The second voice recognizer converts the voice information into second information. The sorter sorts third information and fourth information from the second information. The storage device stores the first information, the third information, and the fourth information. The processor performs processing based on the first information, the third information, and the fourth information. If there are one or two pieces of missing information in the first information, the third information, and the fourth information, the processor complements the missing information by using information stored in the storage device and performs processing.

Abstract: An audio communication endpoint receives a bitstream containing spectral components representing spectral content of an audio signal, wherein the spectral components relate to a first range extending up to a first break frequency, above which any spectral components are unassigned. The endpoint adapts the received bitstream in accordance with a second range extending up to a second break frequency by removing spectral components or adding neutral-valued spectral components relating to a range between the first and second break frequencies. The endpoint then attenuates spectral content in a neighborhood of the least of the first and second break frequencies for thereby achieving a gradual spectral decay. After this, reconstructing the audio signal is reconstructed by an inverse transform operating on spectral components relating to said second range in the adapted and attenuated received bitstream. At small computational expense, the endpoint may to adapt to different sample rates in received bitstreams.

Abstract: Methods and apparatus related to automatically rewriting a string of text utilizing one or more rewrite rules. Some implementations are directed to scoring rewrite rules based at least in part on user interactions with rewrites that are generated by applying the rewrite rules. Some implementations are directed to determining the effectiveness of a rewrite generated based on applying one or more rewrite rules to a string of text. In some of those implementations, the determination may be based at least in part on one or more characteristics of the string of text, one or more characteristics of the rewrite, and/or scores associated with the rewrite rules.

Abstract: As disclosed herein a method, executed by a computer, for enabling enhanced reading device usability includes detecting, on an electronic device, a read operation that audibly reads visually presented information. The method further includes retrieving from a user profile a first threshold value and a second threshold value. The method further includes analyzing potential distractions to determine an estimated distraction level. The method further includes pausing the read operation if the estimated distraction level is greater than or equal to the first threshold value. The method further includes resuming the read operation if the estimated distraction level is less than or equal to the second threshold value. A computer system, and a computer program product corresponding to the method are also disclosed herein.

Abstract: In general, techniques are described for coding of vectors decomposed from higher order ambisonic coefficients. A device comprising a processor and a memory may perform the techniques. The processor may be configured to obtain from a bitstream data indicative of a plurality of weight values that represent a vector that is included in a decomposed version of the plurality of HOA coefficients. Each of the weight values may correspond to a respective one of a plurality of weights in a weighted sum of code vectors that represents the vector and that includes a set of code vectors. The processor may further be configured to reconstruct the vector based on the weight values and the code vectors. The memory may be configured to store the reconstructed vector.

Abstract: As disclosed herein a method, executed by a computer, for enabling enhanced reading device usability includes detecting, on an electronic device, a read operation that audibly reads visually presented information. The method further includes retrieving from a user profile a first threshold value and a second threshold value. The method further includes analyzing potential distractions to determine an estimated distraction level. The method further includes pausing the read operation if the estimated distraction level is greater than or equal to the first threshold value. The method further includes resuming the read operation if the estimated distraction level is less than or equal to the second threshold value. A computer system, and a computer program product corresponding to the method are also disclosed herein.

Abstract: A system, computer program product, and process are provided for an automated escalation agent. A receiver receives a request for language interpretation from a first language to a second language. Further, a database stores data associated with a plurality of language interpreters associated with a computer implemented language interpretation platform. A processor searches the database and determines that no online language interpreter is available to perform language interpretation at a time of the request and that escalates the request to determine if an offline language interpreter is available to initiate the language interpretation within a predetermined time period measured from the time of the request. An automated escalation agent module searches the database according to notification criteria, and sends at least one notification including the request to a plurality of offline language interpreters that meet the notification criteria.

Abstract: Example embodiments include a method of reducing noise include forming a main signal and one or more reference signals at a beam-former based on at least two received audio signals, detecting voice activity at a voice activity detector, where the voice activity detector receives the main and reference signals and outputting a desired voice activity signal, adaptively cancelling noise at an adaptive noise canceller, where the adaptive noise canceller receives the main, reference, and desired voice activity signals and outputs an adaptive noise cancellation signal, and reducing noise at a noise reducer receiving the desired voice activity and adaptive noise cancellation signals and outputting a desired speech signal.

Abstract: An electronic apparatus and a controlling methods thereof are disclosed. The electronic apparatus includes a voice input unit configured to receive a user voice, a storage unit configured to store a plurality of voice print feature models representing a plurality of user voices and a plurality of utterance environment models representing a plurality of environmental disturbances, a controller, in response to a user voice being input through the voice input unit, configured to extract utterance environment information of an utterance environment model among the plurality of utterance environment models corresponding to a location where the user voice is input, compare a voice print feature of the input user voice with the plurality of voice print feature models, revise a result of the comparison based on the extracted utterance environment information, and recognize a user corresponding to the input user voice based on the revised result.

Abstract: Systems and methods for addressing missing features in models are provided. In some implementations, a model configured to indicate likelihoods of different outcomes is accessed. The model includes a respective score for each of a plurality of features, and each feature corresponds to an outcome in an associated context. It is determined that the model does not include a score for a feature corresponding to a potential outcome in a particular context. A score is determined for the potential outcome in the particular context based on the scores for one or more features in the model that correspond to different outcomes in the particular context. The model and the score are used to determine a likelihood of occurrence of the potential outcome.

Abstract: A sample counter in each channel performs counting operation at a given rate. Independently for each channel, the rate and an initial value for the counter are set, and start and stop of the counting operation of the counter are controlled, so that a partial portion of an original waveform corresponding to a count range from the set initial value to a count stop point is reproduced in the channel. A control section sets the initial values in individual ones of a set of channels, selected from among the channels, such that sample values at different sample positions of the original waveform are simultaneously retrieved in individual ones of the set of channels, and controls an overlap adder to add up the retrieved sample values, so that sample values of an audio waveform signal with a plurality of partial portions of the original waveform, partially overlapping each other are output.

Abstract: A method of compressing the audio dynamics of an audio signal. The method includes a step of acquiring an audio signal; a step of selecting a first instant of the audio signal; a step of calculating a plurality of partial gains corresponding, respectively, to a plurality of observation windows of the audio signal that are centered on the first instant, the width of the observation windows following a geometric progression with a rate and first term that are predefined; a step of summing the partial gains calculated in a first corrective term; and a step of applying the first corrective term to the audio signal at the first instant.

Abstract: The voice recognition processing apparatus includes a voice acquirer, a first voice recognizer, a storage device, and a recognition result determiner. The voice acquirer acquires a user's voice, and outputs voice information. The first voice recognizer converts the voice information into first information. The storage device previously stores a dictionary in which an exclusion vocabulary is registered. The recognition result determiner compares the first information with the exclusion vocabulary to determine whether the first information includes a word that agrees with a word included in the exclusion vocabulary. The recognition result determiner determines that the first information is information to be rejected, when the first information includes the word that agrees with a word included in the exclusion vocabulary, and determines that the first information is information to be executed, when the first information does not include the word that agrees with a word included in the exclusion vocabulary.

Abstract: At least one spoken utterance and a stored vehicle acoustic impulse response can be provided to a computing device. The computing device is programmed to provide at least one speech file based at least in part on the spoken utterance and the vehicle acoustic impulse response.

Abstract: A method, apparatus and non-transitory computer readable storage medium, in one embodiment, interpreting at least one input from a user via a wireless device, receiving at least one user account with the at least one input, deriving at least one representation of user intent, identifying at least one task based on the at least one representation of user intent, contacting at least one service to perform the identified at least one task and synthesizing speech to communicate a result of the contact to the wireless device.

Abstract: A system, article, and method of automatic speech recognition with dynamic vocabularies is described herein.

Abstract: A system and method for representing quasi-periodic waveforms, for example, representing a plurality of limited decompositions of the quasi-periodic waveform. Each decomposition includes a first and second amplitude value and at least one time value. In some embodiments, each of the decompositions is phase adjusted such that the arithmetic sum of the plurality of limited decompositions reconstructs the quasi-periodic waveform. Data-structure attributes are created and used to reconstruct the quasi-periodic waveform. Features of the quasi-periodic wave are tracked using pattern-recognition techniques. The fundamental rate of the signal (e.g., heartbeat) can vary widely, for example by a factor of 2-3 or more from the lowest to highest frequency. To get quarter-phase representations of a component (e.g.

Abstract: A desired character train included in a predefined reference character train, such as lyrics, is set as a target character train, and a user designates a target phoneme train that is indirectly representative of the target character train by use of a limited plurality of kinds of particular phonemes, such as vowels and a particular consonants. A reference phoneme train indirectly representative of the reference character train by use of the particular phonemes is prepared in advance. Based on a comparison between the target phoneme train and the reference phoneme train, a sequence of the particular phonemes in the reference phoneme train that matches the target phoneme train is identified, and a character sequence in the reference character train that corresponds to the identified sequence of the particular phonemes is identified. The thus-identified character sequence estimates the target character train.

Abstract: To recombine incorrectly separated tokens in NLP, a determination is made whether a token from an ordered set of tokens is present in a dictionary related to a corpus from which the ordered set is extracted. When the token is not present in the dictionary, and when a compounding threshold has not been reached, the token is agglutinated with a next adjacent token in the ordered set to form the compound token. The compounding threshold limits a number of tokens that can be agglutinated to form a compound token. A determination is made whether the compound token is present in the dictionary. A weight is assigned to the compound token when the compound token is present in the dictionary and a confidence rating of the compound token is computed as a function of the weight. The compound token and the confidence rating are used in NLP of the corpus.

Abstract: A voice processing apparatus includes a voice quality determining unit configured to determine a target speaker determining method used for a voice quality conversion in accordance with a determining method control value for instructing the target speaker determining method of determining a target speaker whose voice quality is targeted to the voice quality conversion, and determine the target speaker in accordance with the target speaker determining method.