Abstract: A path-switchable dual polarization controller includes an input polarization beam splitter (PBS) switchably connected to either one of two optical controllers configured to tunably remix polarization components received from the PBS to obtain two target polarization components of input light. When one of the optical controllers requires a reset, PBS outputs are switched to the other optical controller, and the first optical controller is reset offline. The circuit may be used for polarization demultiplexing.

Abstract: A path-switchable dual polarization controller includes an input polarization beam splitter (PBS) switchably connected to either one of two optical controllers configured to tunably remix polarization components received from the PBS to obtain two target polarization components of input light. When one of the optical controllers requires a reset, PBS outputs are switched to the other optical controller, and the first optical controller is reset offline. The circuit may be used for polarization demultiplexing.

Abstract: Robust, multi-faceted sub-word method for rapidly and reliably detecting a barge-in condition of a speaker talking while an automated audio prompt is being played. This sub-word method allows for rapid stopping of the prompt to improve automatic speech recognition and reduce speaker confusion and/or frustration. An automatic speech recognition system (ASR) that practices such a method is also presented.

Abstract: The apparatus, method and system of the present invention provide for cross-speaker speech recognition, and are particularly suited for telecommunication applications such as automatic name (voice) dialing, message management, call return management, and incoming call screening. The method of the present invention includes receiving incoming speech, such as an incoming caller name, and generating a phonetic transcription of the incoming speech with a speaker-independent, hidden Markov model having an unconstrained grammar in which any phoneme may follow any other phoneme, followed by determining a transcription parameter as a likelihood of fit of the incoming speech to the speaker-independent model.

Abstract: An automated speech recognition system comprises a preprocessor, a speech recognizer, and a task-independent utterance verifier. The task independent utterance verifier employs a first subword acoustic Hidden Markov Model for determining a first likelihood that a speech segment contains a sound corresponding to a speech recognition hypothesis, and a second anti-subword acoustic Hidden Markov Model for determining a second likelihood that a speech segment contains a sound other than one corresponding to the speech recognition hypothesis. In operation, the utterance verifier employs the subword and anti-subword models to produce for each recognized subword in the input speech the first and second likelihoods. The utterance verifier determines a subword verification score as the log of the ratio of the first and second likelihoods.

Abstract: Speech recognition technology has attained maturity such that the most likely speech recognition result has been reached and is available before an energy based termination of speech has been made. The present invention innovatively uses the rapidly available speech recognition results to provide intelligent barge-in for voice-response systems, to count words to output sub-sequences to provide paralleling and/or pipelining of tasks related to the entire word sequence, and to count words to provide rapid, speech recognition based termination of speech processing and outputting of the recognized word sequence.

Abstract: A speech recognition method and apparatus which has a first stage to provide keyword hypotheses and a second stage to provide testing of those hypotheses by utterance verification. The utterance verification used has three separate models for each word: one keyword verification model, one misrecognition verification model, and one non-keyword verification model. Further, all three are developed independently of the recognizer keyword models. Because of this independence, the three verification models can be iteratively trained using existing speech data bases to jointly provide a minimum amount of verification errors.

Abstract: A new speaker verification method, termed Mixture Decomposition Discrimination (MDD), and a new apparatus for using MDD are presented. MDD takes mixture component score information from a speaker independent recognizer and transmits this information while it is still decomposed as a mixture of component scores that indicate the response of the states of a Hidden Markov Model (HMM) before this information is combined into a single speaker independent recognizer parameter. MDD can be very effective in improving the performance of existing verification methods based on speaker dependent HMMs with cohort normalization because the errors of the two speaker verification methods are very uncorrelated statistically. Experimental results have shown that when MDD is incorporated into a system that also uses speaker dependent HMMs, the resulting hybrid system has its average equal error rate reduced by 46% compared to cohort normalized speaker independent HMMs.

Abstract: A verification system to determine unknown input speech contains a recognized keyword or consists of speech or other sounds that do not contain any of the keywords. The verification system is designed to operate on the subword level, so that the verification process is advantageously vocabulary independent. Such a vocabulary-independent verifier is achieved by a two-stage verification process comprising subword level verification followed by string level verification. The subword level verification stage verifies each subword segment in the input speech as determined by an Hidden Markov Model recognizer to determine if that segment consists of the sound corresponding to the subword that the HMM recognizer assigned to that segment. The string level verification stage combines the results of the subword level verification to make the rejection decision for the whole keyword.

Abstract: Speech recognition technology has attained maturity such that the most likely speech recognition result has been reached and is available before an energy based termination of speech has been made. The present invention innovatively uses the rapidly available speech recognition results to provide intelligent barge-in for voice-response systems, to count words to output sub-sequences to provide paralleling and/or pipelining of tasks related to the entire word sequence, and to count words to provide rapid, speech recognition based termination of speech processing and outputting of the recognized word sequence.