Abstract
This paper proposes an articulatory feature-based conditional pronunciation modeling (AFCPM) technique for speaker verification. The technique models the pronunciation behaviors of speakers by creating a link between the actual phones produced by the speakers and the state of articulations during speech production. Speaker models consisting of conditional probabilities of two articulatory classes are adapted from a set of universal background models (UBMs) using MAP adaptation technique. This adaptation approach aims to prevent over-fitting the speaker models when the amount of speaker data is insufficient for a direct estimation. Experimental results show that the adaptation technique can enhance the discriminating power of speaker models by establishing a tighter coupling between speaker models and the UBMs. Results also show that fusing the scores derived from an AFCPM-based system and a conventional spectral-based system achieves a significantly lower error rate than that of the individual systems. This suggests that AFCPM and spectral features are complementary to each other.
Original language | English |
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Title of host publication | 2004 International Symposium on Chinese Spoken Language Processing - Proceedings |
Pages | 61-64 |
Number of pages | 4 |
Publication status | Published - 1 Dec 2004 |
Event | 2004 International Symposium on Chinese Spoken Language Processing - Hong Kong, China, Hong Kong Duration: 15 Dec 2004 → 18 Dec 2004 |
Conference
Conference | 2004 International Symposium on Chinese Spoken Language Processing |
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Country/Territory | Hong Kong |
City | Hong Kong, China |
Period | 15/12/04 → 18/12/04 |
ASJC Scopus subject areas
- General Engineering