Discriminative training of multi-state barge-in models for...

Details Discriminative training of multi-state barge-in models for... Discriminative training of multi-state barge-in models for...

2011-08-16

2011-08-16

Yen, Eric (Department: 2626)

Data processing: speech signal processing, linguistics, language

Speech signal processing

Application

C704S233000, C704S250000, C704S255000, C704S270000

Reexamination Certificate

active

08000971

ABSTRACT:
Disclosed are systems and methods for training a barge-in-model for speech processing in a spoken dialogue system comprising the steps of (1) receiving an input having at least one speech segment and at least one non-speech segment, (2) establishing a restriction of recognizing only speech states during speech segments of the input and non-speech states during non-speech segments of the input, (2) generating a hypothesis lattice by allowing any sequence of speech Hidden Markov Models (HMMs) and non-speech HMMs, (4) generating a reference lattice by only allowing speech HMMs for at least one speech segment and non-speech HMMs for at least one non-speech segment, wherein different iterations of training generates at least one different reference lattice and at least one reference transcription, and (5) employing the generated reference lattice as the barge-in-model for speech processing.

REFERENCES:
patent: 6725199 (2004-04-01), Brittan et al.
patent: 6801604 (2004-10-01), Maes et al.
patent: 6934756 (2005-08-01), Maes
patent: 6947895 (2005-09-01), Shanmugham
patent: 7047197 (2006-05-01), Bennett
patent: 7058577 (2006-06-01), Surace et al.
patent: 7203721 (2007-04-01), Ben-Efraim et al.

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