HKUST Library Institutional Repository Banner

HKUST Institutional Repository >
Electronic and Computer Engineering  >
ECE Conference Papers >

Please use this identifier to cite or link to this item:
Title: Decision tree-based triphones are robust and practical for Mandarian speech recognition
Authors: Liu, Yi
Fung, Pascale N.
Keywords: Speech recognition systems
Decision tree-based clustering
Issue Date: 1999
Citation: Proceedings 6th European Conference on Speech Communication and Technology (Eurospeech 99), Budapest, Hungary, September 5-9, 1999, p. 895-898
Abstract: In large-vocabulary, speaker-independent speech recognition systems, modeling of vocabulary words by subword units is mandatory. This paper studies the use of triphone units for Mandarin speech recognition compared to biphone and context-independent phonetic units. In order to solve unseen triphones in speech recognition, decision-tree based clustering is used in triphone units. This method achieves high recognition performance with limited training data and also reduces the model training time. The robustness and effectiveness of the cross-word, tree-based triphone units have been proved by the speaker-independent continuous Manadarin speech recognition task. The training computation time reduces by about 2.3 times after trying states for triphone models, the recognition syllable accuracy increase 28.7% compared to monophone units and by 13.5% compared to biphone units.
Rights: We would like to give credit to International Speech Communication Association for granting us permission to repost this article.
Appears in Collections:HLTC Conference Papers
ECE Conference Papers

Files in This Item:

File Description SizeFormat
deci.pdfpre-published version477KbAdobe PDFView/Open

All items in this Repository are protected by copyright, with all rights reserved.