Speech recognition method

Details Speech recognition method Speech recognition method

2005-07-12

2005-07-12

Abebe, Daniel (Department: 2655)

Data processing: speech signal processing, linguistics, language

Speech signal processing

Recognition

C704S256000

Reexamination Certificate

active

06917919

ABSTRACT:
A speech recognition method is described in which a basic set of models is adapted to a current speaker on account of the speaker's already noticed speech data. The basic set of models comprises models for different acoustic units. The models are described each by a plurality of model parameters. The basic set of models is then represented by a supervector in a high-dimensional vector space (model space), the supervector being formed by a concatenation of the plurality of the model parameters of the models of the basic set of models. The adaptation of this basic set of models to the speaker is effected in the model space by means of a MAP method in which an asymmetric distribution in the model space is selected as an a priori distribution for the MAP method.

REFERENCES:
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Botterweck: “Anisotropic MAP defined by eigenvoices for large vocabulary continuous speech recognition” 2001 IEEE Internationa Conference on Acoustics, Speech, And Signal Processing. Proceedings (Cat. No. 01ch37221), May 7-11, 2001, vol. 1, pp. 353-356.

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