Candidate generation for ASR output error correction using a Context-Dependent Syllable Cluster-based Confusion Matrix

Chao Hong Liu, Chung-Hsien Wu, David Sarwono, Jhing Fa Wang

Research output: Contribution to journalConference article

1 Citation (Scopus)

Abstract

Error correction techniques have been proposed in the applications of language learning and spoken dialogue systems for spoken language understanding. These techniques include two consecutive stages: the generation of correction candidates and the selection of correction candidates. In this study, a Context-Dependent Syllable Cluster (CD-SC)-based Confusion Matrix is proposed for the generation of correction candidates. A Contextual Fitness Score, measuring the sequential relationship to the neighbors of the candidate, is proposed for corrected syllable sequence selection. Finally, the n-gram language model is used to determine the final word sequence output. Experiments show that the proposed method improved from 0.742 to 0.771 in terms of BLEU score as compared to the conventional speech recognition mechanism.

Original languageEnglish
Pages (from-to)1633-1636
Number of pages4
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Publication statusPublished - 2011 Dec 1
Event12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011 - Florence, Italy
Duration: 2011 Aug 272011 Aug 31

All Science Journal Classification (ASJC) codes

  • Language and Linguistics
  • Human-Computer Interaction
  • Signal Processing
  • Software
  • Modelling and Simulation

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