Utterance Verification Using State-Level Log-Likelihood Ratio with Frame and State Selection

This paper suggests utterance verification system using state-level log-likelihood ratio with frame and state selection. We use hidden Markov models for speech recognition and utterance verification as acoustic models and anti-phone models. The hidden Markov models have three states and each state represents different characteristics of a phone. Thus we propose an algorithm to compute state-level log-likelihood ratio and give weights on states for obtaining more reliable confidence measure of recognized phones. Additionally, we propose a frame selection algorithm to compute confidence measure on frames including proper speech in the input speech. In general, phone segmentation information obtained from speaker-independent speech recognition system is not accurate because triphone-based acoustic models are difficult to effectively train for covering diverse pronunciation and coarticulation effect. So, it is more difficult to find the right matched states when obtaining state segmentation information. A state selection algorithm is suggested for finding valid states. The proposed method using state-level log-likelihood ratio with frame and state selection shows that the relative reduction in equal error rate is 18.1 % compared to the baseline system using simple phone-level log-likelihood ratios.
Publisher
IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
Issue Date
2010-03
Language
ENG
Keywords

CONFIDENCE MEASURES; SPEECH RECOGNITION

Citation

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, v.E93D, no.3, pp.647 - 650

ISSN
0916-8532
DOI
10.1587/transinf.E93.D.647
URI
http://hdl.handle.net/10203/23723
Appears in Collection
EE-Journal Papers(저널논문)
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