Transcription of speech data with segments from acoustically dis

Data processing: speech signal processing – linguistics – language – Speech signal processing – Recognition

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704242, G10L 1520

Patent

active

060675179

ABSTRACT:
A technique to improve the recognition accuracy when transcribing speech data that contains data from a wide range of environments. Input data in many situations contains data from a variety of sources in different environments. Such classes include: clean speech, speech corrupted by noise (e.g., music), non-speech (e.g., pure music with no speech), telephone speech, and the identity of a speaker. A technique is described whereby the different classes of data are first automatically identified, and then each class is transcribed by a system that is made specifically for it. The invention also describes a segmentation algorithm that is based on making up an acoustic model that characterizes the data in each class, and then using a dynamic programming algorithm (the viterbi algorithm) to automatically identify segments that belong to each class. The acoustic models are made in a certain feature space, and the invention also describes different feature spaces for use with different classes.

REFERENCES:
patent: 4430726 (1984-02-01), Kasday
patent: 5333275 (1994-07-01), Wheatley et al.
patent: 5579436 (1996-11-01), Chou et al.

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