Abstract: A system and method for tuning a speech recognition engine to an individual microphone using a database containing acoustical models for a plurality of microphones. Microphone performance characteristics are obtained from a microphone at a speech recognition engine, the database is searched for an acoustical model that matches the characteristics, and the speech recognition engine is then modified based on the matching acoustical model.

Abstract: A method of and system for transient noise rejection for improved speech recognition. The method comprises the steps of (a) receiving audio including user speech and at least some transient noise associated with the speech, (b) converting the received audio into digital data, (c) segmenting the digital data into acoustic frames, and (d) extracting acoustic feature vectors from the acoustic frames. The method also comprises the steps of (e) evaluating the acoustic frames for transient noise on a frame-by-frame basis, (f) rejecting those acoustic frames having transient noise, (g) accepting as speech frames those acoustic frames having no transient noise and, thereafter, (h) recognizing the user speech using the speech frames.

Abstract: A method of operating a vehicle telematics unit includes determining the location of a vehicle equipped with a vehicle telematics unit; determining if telematics dialing software operated by the vehicle telematics unit includes a verbal dialing protocol used at the determined vehicle location; if not, identifying one or more verbal dialing protocols used at the determined location of the vehicle; requesting telematics dialing software that includes the one or more identified verbal dialing protocols; receiving the requested telematics dialing software from a central facility; and storing the received telematics dialing software at the vehicle.

Abstract: A method of speech recognition in a vehicle. Audio including noise and a speech signal representative of an utterance from a user is received via a microphone, and a signal-to-noise ratio (SNR) for the received audio is calculated using a processor. It is determined whether the calculated SNR is greater than a predetermined SNR. If so, then a noise distribution is identified for addition to the received audio, and noise corresponding to the identified noise distribution is injected into the received audio to produce noise-injected audio including the speech signal.

Abstract: A method of and system for automated distortion classification. The method includes steps of (a) receiving audio including a user speech signal and at least some distortion associated with the signal; (b) pre-processing the received audio to generate acoustic feature vectors; (c) decoding the generated acoustic feature vectors to produce a plurality of hypotheses for the distortion; and (d) post-processing the plurality of hypotheses to identify at least one distortion hypothesis of the plurality of hypotheses as the received distortion. The system can include one or more distortion models including distortion-related acoustic features representative of various types of distortion and used by a decoder to compare the acoustic feature vectors with the distortion-related acoustic features to produce the plurality of hypotheses for the distortion.

Abstract: A method of evaluating attributes of synthesized speech. The method includes processing a text input into a synthesized speech utterance using a processor of a text-to-speech system, applying a human speech utterance to a speech model to obtain a reference wherein the human speech utterance corresponds to the text input, applying the synthesized speech utterance to at least one of the speech model or an other speech model to obtain a test, and calculating a difference between the test and the reference. The method also can be used in a speech synthesis method.

Abstract: A method and system of speech synthesis. A text input is received in a text-to-speech system and, using a processor of the system, the text input is processed into synthesized speech which is established as unintelligible. The text input is reprocessed into subsequent synthesized speech and output to a user via a loudspeaker to correct the unintelligible synthesized speech. In one embodiment, the synthesized speech can be established as unintelligible by predicting intelligibility of the synthesized speech, and determining that the predicted intelligibility is lower than a minimum threshold. In another embodiment, the synthesized speech can be established as unintelligible by outputting the synthesized speech to the user via the loudspeaker, and receiving an indication from the user that the synthesized speech is not intelligible.

Abstract: A method for recognizing speech involves reciting, into a speech recognition system, an utterance including a numeric sequence that contains a digit string including a plurality of tokens and detecting a co-articulation problem related to at least two potentially co-articulated tokens in the digit string. The numeric sequence may be identified using i) a dynamically generated possible numeric sequence that potentially corresponds with the numeric sequence, and/or ii) at least one supplemental acoustic model. Also disclosed herein is a system for accomplishing the same.

Abstract: Methods of automatic speech recognition for premature enunciation. In one method, a) a user is prompted to input speech, then b) a listening period is initiated to monitor audio via a microphone, such that there is no pause between the end of step a) and the beginning of step b), and then the begin-speaking audible indicator is communicated to the user during the listening period. In another method, a) at least one audio file is played including both a prompt for a user to input speech and a begin-speaking audible indicator to the user, b) a microphone is activated to monitor audio, after playing the prompt but before playing the begin-speaking audible indicator in step a), and c) speech is received from the user via the microphone.

Abstract: A method of automatic speech recognition. An utterance is received from a user in reply to a text message, via a microphone that converts the reply utterance into a speech signal. The speech signal is processed using at least one processor to extract acoustic data from the speech signal. An acoustic model is identified from a plurality of acoustic models to decode the acoustic data, and using a conversational context associated with the text message. The acoustic data is decoded using the identified acoustic model to produce a plurality of hypotheses for the reply utterance.

Abstract: A method of automatic speech recognition includes receiving an utterance from a user via a microphone that converts the utterance into a speech signal, pre-processing the speech signal using a processor to extract acoustic data from the received speech signal, and identifying at least one user-specific characteristic in response to the extracted acoustic data. The method also includes determining a user-specific confidence threshold responsive to the at least one user-specific characteristic, and using the user-specific confidence threshold to recognize the utterance received from the user and/or to assess confusability of the utterance with stored vocabulary.

Abstract: A speech signal processing system and method which uses the following steps: (a) receiving an utterance from a user via a microphone that converts the utterance into a speech signal; and (b) pre-processing the speech signal using a processor. The pre-processing step includes extracting acoustic data from the received speech signal, determining from the acoustic data whether the utterance includes one or more obstruents; estimating speech energy from higher frequencies associated with the identified obstruents, and mapping the estimated speech energy to lower frequencies.

Abstract: A method of operating a vehicle telematics unit includes determining the location of a vehicle equipped with a vehicle telematics unit; determining if telematics dialing software operated by the vehicle telematics unit includes a verbal dialing protocol used at the determined vehicle location; if not, identifying one or more verbal dialing protocols used at the determined location of the vehicle; requesting telematics dialing software that includes the one or more identified verbal dialing protocols; receiving the requested telematics dialing software from a central facility; and storing the received telematics dialing software at the vehicle.

Abstract: A method of generating proxy acoustic models for use in automatic speech recognition includes training acoustic models from speech received via microphone from male speakers of a first language, and adapting the acoustic models in response to language-independent speech data from female speakers of a second language, to generate proxy acoustic models for use during runtime of speech recognition of an utterance from a female speaker of the first language.

Abstract: Automatic speech recognition including receiving speech via a microphone, pre-processing the received speech to generate acoustic feature vectors, classifying dialect of the received speech, selecting at least one of an acoustic model or a lexicon specific to the classified dialect, decoding the acoustic feature vectors using a processor and at least one of the selected dialect-specific acoustic model or selected lexicon to produce a plurality of hypotheses for the received speech, and post-processing the plurality of hypotheses to identify one of the plurality of hypotheses as the received speech.

Abstract: A method of and system for speech synthesis. First and second text inputs are received in a text-to-speech system, and processed into respective first and second speech outputs corresponding to stored speech respectively from first and second speakers using a processor of the system. The second speech output of the second speaker is adapted to sound like the first speech output of the first speaker.

Abstract: A method of and system for transient noise rejection for improved speech recognition. The method comprises the steps of (a) receiving audio including user speech and at least some transient noise associated with the speech, (b) converting the received audio into digital data, (c) segmenting the digital data into acoustic frames, and (d) extracting acoustic feature vectors from the acoustic frames. The method also comprises the steps of (e) evaluating the acoustic frames for transient noise on a frame-by-frame basis, (f) rejecting those acoustic frames having transient noise, (g) accepting as speech frames those acoustic frames having no transient noise and, thereafter, (h) recognizing the user speech using the speech frames.

Abstract: A dialing mode of a telematics unit in a vehicle is controlled by monitoring for dialing digits from a vehicle occupant, determining whether the type of dialing digits are continuous dialing digits or discrete dialing digits, establishing a continuous mode for receiving continuous dialing digits or a discrete mode for receiving discrete dialing digits based on the determination, and if the type of dialing digits changes, switching the established mode.

Abstract: A method of and system for automated distortion classification. The method includes steps of (a) receiving audio including a user speech signal and at least some distortion associated with the signal; (b) pre-processing the received audio to generate acoustic feature vectors; (c) decoding the generated acoustic feature vectors to produce a plurality of hypotheses for the distortion; and (d) post-processing the plurality of hypotheses to identify at least one distortion hypothesis of the plurality of hypotheses as the received distortion. The system can include one or more distortion models including distortion-related acoustic features representative of various types of distortion and used by a decoder to compare the acoustic feature vectors with the distortion-related acoustic features to produce the plurality of hypotheses for the distortion.

Abstract: A method for recognizing speech involves reciting, into a speech recognition system, an utterance including a numeric sequence that contains a digit string including a plurality of tokens and detecting a co-articulation problem related to at least two potentially co-articulated tokens in the digit string. The numeric sequence may be identified using i) a dynamically generated possible numeric sequence that potentially corresponds with the numeric sequence, and/or ii) at least one supplemental acoustic model. Also disclosed herein is a system for accomplishing the same.