Abstract: Echoes caused by discontinuities in a telecommunications transmission lines cause double talk which cause divergence problems with echo cancellers. Divergence problems in echo cancellers cause considerable problems in interactive caller response systems, they cause less problems if all parties to a call are human. One of the biggest problems is the effect of the echoes on automatic speech recognition systems. The echo canceller method and system presented cancels echoes to reduce their interference with ASR and yet provides stability in the presence of double talk.

Abstract: A system and method provide ASR talkoff suppression in a prompt-and collect voice transaction system in which a prompt signal is sent and an input signal is received. A comparison is made of a characteristic of the prompt signal and the input signal. Processing of the input signal to reduce the likelihood of an ASR response thereto is performed if the result of the comparison satisfies a predetermined criterion.

Abstract: An automatic speech recognition system for the condition that an incoming caller's speech is quiet and a resulting echo (of a loud playing prompt) can cause the residual (the portion of the echo remaining after even echo cancellation) to be of the magnitude of the incoming speech input. Such loud echoes can falsely trigger the speech recognition system and interfere with the recognition of valid input speech. An echo model has been proven to alleviate this fairly common problem and to be effective in eliminating such false triggering. Further, this automatic speech recognition system enhanced the recognition of valid speech was provided within an existing hidden Markov modeling framework.

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: 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: 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.