Stress detection based on multi-class probabilistic support vector machines for accented English speech

Jhing Fa Wang, Gung Ming Chang, Jia Ching Wang, Shun Chieh Lin

研究成果: 書貢獻/報告類型會議論文篇章同行評審

5 引文 斯高帕斯(Scopus)

摘要

A stress detection based on multi-class probabilistic support vector machines (MCP-SVMs) is proposed for classifying speech into following categories - no stress, primary stress, and secondary stress. The stress classifier is performed with a feature set including perceptual features, MFCC, delta-MFCC and delta-delta-MFCC. To observe that speakers from the same accent regions had similar tendencies in mispronunciations including word stress, this work uses English Across Taiwan (EAT) to represent Taiwanese-accented English speech corpora. The overall performance in the experimental results achieves about 84% classification of accuracy.

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主出版物標題2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009
頁面346-350
頁數5
DOIs
出版狀態已出版 - 2009
事件2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009 - Los Angeles, CA, United States
持續時間: 31 3月 20092 4月 2009

出版系列

名字2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009
7

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???event.eventtypes.event.conference???2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009
國家/地區United States
城市Los Angeles, CA
期間31/03/092/04/09

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