Connected word talker verification using whole word hidden Markov models

Authors:
A. E. Rosenberg;C.-H. Lee;S. Gokcen
Affiliations:
AT& T Bell Labs., Murray Hill, NJ, USA;AT& T Bell Labs., Murray Hill, NJ, USA;AT& T Bell Labs., Murray Hill, NJ, USA
Venue:
ICASSP '91 Proceedings of the Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference
Year:
1991

Citing 0
Cited 3

Limited parameter hidden Markov models for connected digit speaker verification over telephone channels

ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: speech processing - Volume II
Speaker identification experiments using HMMs

ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: speech processing - Volume II
Constrained temporal structure for text-dependent speaker verification

Digital Signal Processing

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Abstract

A speaker verification system using connected word verification phrases has been implemented and studied. Verification utterances are represented as concatenated speaker-dependent whole-word hidden Markov models (HMMs). Verification phrases are specified as strings of words drawn from a small fixed vocabulary, such as the digits. Phrases can either be individualized or randomized for greater security. Training techniques to create speaker-dependent models for verification are used in which initial word models are created by bootstrapping from existing speaker-independent models. The system has been evaluated on a 20-speaker telephone database of connected digital utterances. Using approximately 66 s of connected digit training utterances per speaker, the verification equal-error rate is approximately 3.5% for 1.1 s test utterances and 0.3% for 4.4 s test utterances. In comparison, the performance of a template-based system using the same amount of training data is 6.7% and 1.5%, respectively.