A syllable lattice approach to speaker verification

This paper proposes a syllable-lattice-based speaker verification algorithm for Mandarin Chinese input. For each speech utterance, a syllable lattice is generated with a speaker-independent large-vocabulary continuous speech recognition system in free syllable decoding. The verification decision is made based upon the likelihood ratio between a target-speaker model and a speaker-independent background model, computed on the decoded syllable lattice. The likelihood function is calculated efficiently in a forward algorithm by considering all paths in the lattice. The proposed algorithm was evaluated using a Mandarin Chinese database, where 1832 true and 26 250 impostor trials were recorded by 19 target speakers and 180 impostors. The average duration of each trial is 2 s long without silence. The target-speaker model was adapted from the speaker-independent background model using enrollment data of two minutes with silence. The proposed algorithm achieved an equal-error rate of 0.857% which is beter than 1.21% of the hidden Markov model-based speaker verification algorithm without using syllable lattices. The equal-error rate was further reduced to 0.617% by incorporating the Goussian mixture model-universal background model algorithm with 2048 Gaussian kernels whose equal error rate is 0.990%.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2007-11
Language
ENG
Keywords

HIDDEN MARKOV-MODELS; MANDARIN CHINESE; RECOGNITION; ADAPTATION; SPEECH

Citation

IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, v.15, no.8, pp.2476 - 2484

ISSN
1558-7916
DOI
10.1109/TASL.2007.906181
URI
http://hdl.handle.net/10203/88611
Appears in Collection
EE-Journal Papers(저널논문)
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