Abstract: Speech recognition systems often process speech by employing models and analyzing audio data. An embodiment of the method and corresponding system described herein allow for passive monitoring of, for example, conversation between user(s) to determine context to use to prime model(s) for later speech recognition requests submitted to the speech recognition system. The embodiment improves the results of the speech recognition system by updating speech recognition model(s) with contextual information of the conversation. This increases the probability that the speech recognition system interprets the conversation to contextually relevant information.

Abstract: In some embodiments, the recognition results produced by a speech processing system (which may include two or more recognition results, including a top recognition result and one or more alternative recognition results) based on an analysis of a speech input, are evaluated for indications of potential significant errors. In some embodiments, the recognition results may be evaluated to determine whether a meaning of any of the alternative recognition results differs from a meaning of the top recognition result in a manner that is significant for a domain, such as the medical domain. In some embodiments, words and/or phrases that may be confused by an ASR system may be determined and associated in sets of words and/or phrases. Words and/or phrases that may be determined include those that change a meaning of a phrase or sentence when included in the phrase/sentence.

Abstract: Described herein are techniques for determining corresponding positions between different representations of a textual work. In some of the techniques, portions of one or more representations may be processed. A determination of a corresponding position may be made in response to a request received from a user, such as a reader that desires to switch between representations. The request may indicate a position in one representation and the representation to which the user would like to switch. In response to receiving the request, one or more portions of one or more representations of a textual work may be processed. In some techniques, a corresponding position between different representations may be determined without processing the entirety of one or more representations of the textual work. For example, a corresponding position may be determined without processing an entire audio representation.

Abstract: In some embodiments, the recognition results produced by a speech processing system (which may include two or more recognition results, including a top recognition result and one or more alternative recognition results) based on an analysis of a speech input, are evaluated for indications of potential significant errors. In some embodiments, the recognition results may be evaluated to determine whether a meaning of any of the alternative recognition results differs from a meaning of the top recognition result in a manner that is significant for a domain, such as the medical domain. In some embodiments, words and/or phrases that may be confused by an ASR system may be determined and associated in sets of words and/or phrases. Words and/or phrases that may be determined include those that change a meaning of a phrase or sentence when included in the phrase/sentence.

Abstract: Described herein are techniques for determining corresponding positions between different representations of a textual work. In some of the techniques, portions of one or more representations may be processed. A determination of a corresponding position may be made in response to a request received from a user, such as a reader that desires to switch between representations. The request may indicate a position in one representation and the representation to which the user would like to switch. In response to receiving the request, one or more portions of one or more representations of a textual work may be processed. In some techniques, a corresponding position between different representations may be determined without processing the entirety of one or more representations of the textual work. For example, a corresponding position may be determined without processing an entire audio representation.

Abstract: Described herein are techniques for determining corresponding positions between different representations of a textual work. In some of the techniques, portions of one or more representations may be processed. A determination of a corresponding position may be made in response to a request received from a user, such as a reader that desires to switch between representations. The request may indicate a position in one representation and the representation to which the user would like to switch. In response to receiving the request, one or more portions of one or more representations of a textual work may be processed. In some techniques, a corresponding position between different representations may be determined without processing the entirety of one or more representations of the textual work. For example, a corresponding position may be determined without processing an entire audio representation.

Abstract: Some aspects include a method of monitoring an acoustic environment of a mobile device operating in a low power mode, the mobile device having a first and second processor, the method comprises receiving acoustic input while the mobile device is operating in the low power mode, performing at least one first processing stage on the acoustic input using the first processor, prior to engaging the second processor, to evaluate whether the acoustic input includes a voice command, performing at least one second processing stage on the acoustic input using the second processor to evaluate whether the acoustic input includes a voice command if further processing is needed to determine whether the acoustic input includes a voice command, and initiating responding to the voice command when either the at least one first processing stage or the at least one second processing stage determines that the acoustic input includes a voice command.

Abstract: In some embodiments, the recognition results produced by a speech processing system (which may include two or more recognition results, including a top recognition result and one or more alternative recognition results) based on an analysis of a speech input, are evaluated for indications of potential significant errors. In some embodiments, the recognition results may be evaluated to determine whether a meaning of any of the alternative recognition results differs from a meaning of the top recognition result in a manner that is significant for a domain, such as the medical domain. In some embodiments, words and/or phrases that may be confused by an ASR system may be determined and associated in sets of words and/or phrases. Words and/or phrases that may be determined include those that change a meaning of a phrase or sentence when included in the phrase/sentence.

Abstract: Systems, methods and apparatus for capturing at least one audio signal using a plurality of microphones that generate a plurality of representations of the at least one audio signal. In some embodiments, the plurality of microphones are disposed in a multiple-microphone setting so that the at least one audio signal is captured by at least two of the plurality of microphones. In some embodiments, at least one of the plurality of microphones is a microphone of a mobile device. The plurality of representations of the at least one audio signal may be processed to obtain a processed representation of the at least one audio signal.

Abstract: A mobile device is adapted for automatic speech recognition (ASR). A user interface for interaction with a user includes an input microphone for obtaining speech inputs from the user for automatic speech recognition, and an output interface for system output to the user based on ASR results that correspond to the speech input. A local controller obtains a sample of non-ASR audio from the input microphone for ASR-adaptation to channel-specific ASR characteristics, and then provides a representation of the non-ASR audio to a remote ASR server for server-side adaptation to the channel-specific ASR characteristics, and then provides a representation of an unknown ASR speech input from the input microphone to the remote ASR server for determining ASR results corresponding to the unknown ASR speech input, and then provides the system output to the output interface.

Abstract: In some embodiments, the recognition results produced by a speech processing system (which may include two or more recognition results, including a top recognition result and one or more alternative recognition results) based on an analysis of a speech input, are evaluated for indications of potential significant errors. In some embodiments, the recognition results may be evaluated using one or more sets of words and/or phrases, such as pairs of words/phrases that may include words/phrases that are acoustically similar to one another and/or that, when included in a result, would change a meaning of the result in a manner that would be significant for a domain. The recognition results may be evaluated using the set(s) of words/phrases to determine, when the top result includes a word/phrase from a set of words/phrases, whether any of the alternative recognition results includes any of the other, corresponding words/phrases from the set.

Abstract: According to some aspects, a method of monitoring an acoustic environment of a mobile device, at least one computer readable medium encoded with instructions that, when executed, perform such a method and/or a mobile device configured to perform such a method is provided. The method comprises receiving, by the mobile device, acoustic input from the environment of the mobile device, detecting whether the acoustic input includes a voice command from a user without requiring receipt of an explicit trigger from the user, and initiating responding to the detected voice command.

Abstract: Techniques for improved speech recognition disclosed herein include applying a statistical language model to a free-text input utterance to obtain a plurality of candidate word sequences for automatic speech recognition of the input utterance, each of the plurality of candidate word sequences having a corresponding initial score generated by the statistical language model. For one or more of the plurality of candidate word sequences, each of the one or more candidate word sequences may be analyzed to generate one or more hypotheses for a semantic class of at least one token in the respective candidate word sequence. The initial scores generated by the statistical language model for at least the one or more candidate word sequences may be revised based at least in part on the one or more hypotheses for the semantic class of the at least one token in each of the one or more candidate word sequences.

Abstract: Speech recognition systems often process speech by employing models and analyzing audio data. An embodiment of the method and corresponding system described herein allow for passive monitoring of for example, conversation between user(s) to determine context to use to prime model(s) for later speech recognition requests submitted to the speech recognition system. The embodiment improves the results of the speech recognition system by updating speech recognition model(s) with contextual information of the conversation. This increases the probability that the speech recognition system interprets the conversation to contextually relevant information.

Abstract: Techniques disclosed herein include systems and methods for open-domain voice-enabled searching that is speaker sensitive. Techniques include using speech information, speaker information, and information associated with a spoken query to enhance open voice search results. This includes integrating a textual index with a voice index to support the entire search cycle. Given a voice query, the system can execute two matching processes simultaneously. This can include a text matching process based on the output of speech recognition, as well as a voice matching process based on characteristics of a caller or user voicing a query. Characteristics of the caller can include output of voice feature extraction and metadata about the call. The system clusters callers according to these characteristics. The system can use specific voice and text clusters to modify speech recognition results, as well as modifying search results.

Abstract: A mobile device is described which is adapted for automatic speech recognition (ASR). A speech input receives an unknown speech input signal from a user. A local controller determines if a remote ASR processing condition is met, transforms the speech input signal into a selected one of multiple different speech representation types, and sends the transformed speech input signal to a remote server for remote ASR processing. A local ASR arrangement performs local ASR processing of the speech input including processing any speech recognition results received from the remote server.

Abstract: A mobile device is adapted for protecting private information on the mobile device in a hybrid automatic speech recognition arrangement. The mobile device includes a speech input component for receiving a speech input signal from a user. Additionally, the mobile device includes a local ASR arrangement for performing local ASR processing of the speech input signal and determining if private information is included within the speech input signal. A control unit on the mobile device obscures private information in the speech input signal if the local ASR arrangement identifies information within a speech recognition result as private information. The control unit releases the speech input signal with the obscured private information for transmission to a remote server for further ASR processing. Results from the remote server's ASR processing are integrated and combined with results from local ASR processing to display information on the mobile device.

Abstract: In some embodiments, the recognition results produced by a speech processing system (which may include a top recognition result and one or more alternative recognition results) based on an analysis of a speech input, are evaluated for indications of potential significant errors. In some embodiments, the recognition results may be evaluated to determine whether a meaning of any of the alternative recognition results differs from a meaning of the top recognition result in a manner that is significant for the domain. In some embodiments, one or more of the recognition results may be evaluated to determine whether the result(s) include one or more words or phrases that, when included in a result, would change a meaning of the result in a manner that would be significant for the domain.

Abstract: In some embodiments, recognition results produced by a speech processing system (which may include two or more recognition results, including a top recognition result and one or more alternative recognition results) based on an analysis of a speech input, are evaluated for indications of potential errors. In some embodiments, the indications of potential errors may include discrepancies between recognition results that are meaningful for a domain, such as medically-meaningful discrepancies. The evaluation of the recognition results may be carried out using any suitable criteria, including one or more criteria that differ from criteria used by an ASR system in determining the top recognition result and the alternative recognition results from the speech input. In some embodiments, a recognition result may additionally or alternatively be processed to determine whether the recognition result includes a word or phrase that is unlikely to appear in a domain to which speech input relates.

Abstract: A speech transcription system is described for producing a representative transcription text from one or more different audio signals representing one or more different speakers participating in a speech session. A preliminary transcription module develops a preliminary transcription of the speech session using automatic speech recognition having a preliminary recognition accuracy performance. A speech selection module enables user selection of one or more portions of the preliminary transcription to receive higher accuracy transcription processing. A final transcription module is responsive to the user selection for developing a final transcription output for the speech session having a final recognition accuracy performance for the selected one or more portions which is higher than the preliminary recognition accuracy performance.