HTIMIT and LLHDB: Speech Corpora for the Study of Handset Transducer Effects
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 2 - Volume 2
Corpora for the evaluation of speaker recognition systems
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02
Embedded kernel eigenvoice speaker adaptation and its implication to reference speaker weighting
IEEE Transactions on Audio, Speech, and Language Processing
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Research has shown that speaker verification based on highlevel speaker features requires long enrollment utterances to be reliable. However, in practical speaker verification, it is common to model speakers based a limited amount of enrollment data. To minimize the undesirable effect of insufficient enrollment data on system performance, this paper proposes a new adaptation method for creating speaker models based on high-level features. Different from conventional methods, the proposed adaptation method not only adapts the phoneme-dependent background model but also the phoneme-independent speaker model. The amount of adaptation in the latter is adjusted by a proportional factor derived from the phoneme-independent background models. The proposed method was compared with traditional MAP adaptation under the NIST2000 SRE framework. Experimental results show that the proposed method can solve the data-spareness problem effectively and achieves a better performance when compare with traditional MAP adaptation.