https://scholars.lib.ntu.edu.tw/handle/123456789/632415
Title: | Robust Entropy-based Endpoint Detection for Speech Recognition in Noisy Environments | Authors: | Shen J.-L Hung J.-W LIN-SHAN LEE |
Issue Date: | 1998 | Source: | 5th International Conference on Spoken Language Processing, ICSLP 1998 | Abstract: | This paper presents an entropy-based algorithm for accurate and robust endpoint detection for speech recognition under noisy environments. Instead of using the conventional energy-based features, the spectral entropy is developed to identify the speech segments accurately. Experimental results show that this algorithm outperforms the energy-based algorithms in both detection accuracy and recognition performance under noisy environments, with an average error rate reduction of more than 16%. © 1998. 5th International Conference on Spoken Language Processing, ICSLP 1998. All rights reserved. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-77951493947&partnerID=40&md5=e08c9e95da495acdf329e94404efc684 https://scholars.lib.ntu.edu.tw/handle/123456789/632415 |
SDG/Keyword: | Entropy; Detection accuracy; End point detection; Energy-based; Energy-based algorithms; Entropy-based; Entropy-based algorithm; Noisy environment; Performance; Spectral entropy; Speech segments; Speech recognition |
Appears in Collections: | 電機工程學系 |
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