Method for automatic speaker recognition with hurst...

Details Method for automatic speaker recognition with hurst... Method for automatic speaker recognition with hurst...

2011-03-08

2011-03-08

McFadden, Susan (Department: 2626)

Data processing: speech signal processing, linguistics, language

Speech signal processing

Recognition

Reexamination Certificate

active

07904295

ABSTRACT:
It is proposed a text-independent automatic speaker recognition (ASkR) system which employs a new speech feature and a new classifier. The statistical feature pH is a vector of Hurst parameters obtained by applying a wavelet-based multi-dimensional estimator (M dim wavelets) to the windowed short-time segments of speech. The proposed classifier for the speaker identification and verification tasks is based on the multi-dimensional fBm (fractional Brownian motion) model, denoted by M dim fBm. For a given sequence of input speech features, the speaker model is obtained from the sequence of vectors of H parameters, means and variances of these features.

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Speaker recognition: a Tutorial, Campbell, J.P., Jr.; Proceedings of the IEEE, vol. 85, Issue 9, Sep. 1997 pp. 1437-1462 p. 1438: Generic Speaker Verification. p. 1438: Generic Speaker Verification.

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