Paper: | SP-P11.15 | ||
Session: | Topics in Large Vocabulary Continuous Speech Recognition | ||
Time: | Thursday, May 20, 09:30 - 11:30 | ||
Presentation: | Poster | ||
Topic: | Speech Processing: Confidence Measures/Rejection | ||
Title: | REAL-TIME WORD CONFIDENCE SCORING USING LOCAL POSTERIOR PROBABILITIES ON TREE TRELLIS SEARCH | ||
Authors: | Akinobu Lee; Nara Institute of Science and Technology | ||
Kiyohiro Shikano; Nara Institute of Science and Technology | |||
Tatsuya Kawahara; Kyoto University | |||
Abstract: | Confidence scoring based on word posterior probability is usually performed as a post process of speech recognition decoding, and also needs a large number of word hypotheses to get enough confidence quality. We propose a simple way of computing the word confidence using estimated posterior probability while decoding. At the word expansion of stack decoding search, the local sentence likelihoods that contains heuristic scores of unreached segment are directly used to compute the posterior probabilities. Experimental result showed that, although the likelihoods are not optimal, it can provide slightly better confidence measures compared with N-best lists, while the computation is much faster because no N-best decoding is required. | ||
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