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Front. Inform. Technol. Electron. Eng.  2013, Vol. 14 Issue (11): 835-844    DOI: 10.1631/jzus.C1300104
    
Exploiting articulatory features for pitch accent detection
Junhong Zhao, Ji Xu, Wei-qiang Zhang, Hua Yuan, Jia Liu, Shanhong Xia
State Key Laboratory of Transducer Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100190, China; National Laboratory for Information Science and Technology, Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
Exploiting articulatory features for pitch accent detection
Junhong Zhao, Ji Xu, Wei-qiang Zhang, Hua Yuan, Jia Liu, Shanhong Xia
State Key Laboratory of Transducer Technology, Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100190, China; National Laboratory for Information Science and Technology, Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
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摘要： Articulatory features describe how articulators are involved in making sounds. Speakers often use a more exaggerated way to pronounce accented phonemes, so articulatory features can be helpful in pitch accent detection. Instead of using the actual articulatory features obtained by direct measurement of articulators, we use the posterior probabilities produced by multi-layer perceptrons (MLPs) as articulatory features. The inputs of MLPs are frame-level acoustic features pre-processed using the split temporal context-2 (STC-2) approach. The outputs are the posterior probabilities of a set of articulatory attributes. These posterior probabilities are averaged piecewise within the range of syllables and eventually act as syllable-level articulatory features. This work is the first to introduce articulatory features into pitch accent detection. Using the articulatory features extracted in this way, together with other traditional acoustic features, can improve the accuracy of pitch accent detection by about 2%.
关键词： Articulatory features;  Pitch accent detection;  Prosody;  Computer-aided language learning (CALL);  Multi-layer perceptron (MLP)    
Abstract: Articulatory features describe how articulators are involved in making sounds. Speakers often use a more exaggerated way to pronounce accented phonemes, so articulatory features can be helpful in pitch accent detection. Instead of using the actual articulatory features obtained by direct measurement of articulators, we use the posterior probabilities produced by multi-layer perceptrons (MLPs) as articulatory features. The inputs of MLPs are frame-level acoustic features pre-processed using the split temporal context-2 (STC-2) approach. The outputs are the posterior probabilities of a set of articulatory attributes. These posterior probabilities are averaged piecewise within the range of syllables and eventually act as syllable-level articulatory features. This work is the first to introduce articulatory features into pitch accent detection. Using the articulatory features extracted in this way, together with other traditional acoustic features, can improve the accuracy of pitch accent detection by about 2%.
Key words: Articulatory features    Pitch accent detection    Prosody    Computer-aided language learning (CALL)    Multi-layer perceptron (MLP)
收稿日期: 2013-04-22 出版日期: 2013-11-06
CLC:  TP391  
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Junhong Zhao
Ji Xu
Wei-qiang Zhang
Hua Yuan
Jia Liu
Shanhong Xia

引用本文:

Junhong Zhao, Ji Xu, Wei-qiang Zhang, Hua Yuan, Jia Liu, Shanhong Xia. Exploiting articulatory features for pitch accent detection. Front. Inform. Technol. Electron. Eng., 2013, 14(11): 835-844.

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http://www.zjujournals.com/xueshu/fitee/CN/10.1631/jzus.C1300104    或    http://www.zjujournals.com/xueshu/fitee/CN/Y2013/V14/I11/835

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