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Conference Paper
Word Boundary Unconstraint Viterbi Search For Robust Speech Recognition
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- Authors
- Hoon Chung, Sung Joo Lee, Yun Keun Lee
- Issue Date
- 2009-10
- Citation
- Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) 2009, pp.627-630
- Language
- English
- Type
- Conference Paper
- Abstract
- In this paper, we propose a word boundary unconstraint Viterbi algorithm for robust speech recognition against endpoint detection error on isolated word task domain. In general, onekeyword spotting framework is used to achieve robust recognition by absorbing non-speech events with acoustic filler models. One drawback of such an approach is that there is little improvement or it can even hurt performance if unexpected non-speech events occur, whose spectral characteristics are not trained into acoustic filler models. However, it is unrealistic to prepare acoustic filler models considering all kinds of non-speech events especially occurring in mobile environment. Therefore, we propose another approach where non-speech events are absorbed implicitly by relaxing endpoints constraint of Viterbi algorithm. The experimental results show that the algorithm reduces the word error rate from 80.2% to 10.6% for inaccurately endpoint-detected utterances while consuming a little more computation.
- KSP Keywords
- End Point Detection(EPD), Non-speech, Robust recognition, Spectral characteristics, Speech events, Viterbi Algorithm, detection error, isolated word, mobile environment, robust speech recognition, word error rate