A Hybrid Speech Emotion Recognition System Based on Spectral and Prosodic Features

• ZHOU Yu

  Institute of Acoustics, Chinese Academy of Sciences

• LI Junfeng

  School of Information Science, Japan Advanced Institute of Science and Technology

• SUN Yanqing

  Institute of Acoustics, Chinese Academy of Sciences

• ZHANG Jianping

  Institute of Acoustics, Chinese Academy of Sciences

• YAN Yonghong

  Institute of Acoustics, Chinese Academy of Sciences

• AKAGI Masato

  School of Information Science, Japan Advanced Institute of Science and Technology

抄録

In this paper, we present a hybrid speech emotion recognition system exploiting both spectral and prosodic features in speech. For capturing the emotional information in the spectral domain, we propose a new spectral feature extraction method by applying a novel non-uniform subband processing, instead of the mel-frequency subbands used in Mel-Frequency Cepstral Coefficients (MFCC). For prosodic features, a set of features that are closely correlated with speech emotional states are selected. In the proposed hybrid emotion recognition system, due to the inherently different characteristics of these two kinds of features (e.g., data size), the newly extracted spectral features are modeled by Gaussian Mixture Model (GMM) and the selected prosodic features are modeled by Support Vector Machine (SVM). The final result of the proposed emotion recognition system is obtained by combining the results from these two subsystems. Experimental results show that (1) the proposed non-uniform spectral features are more effective than the traditional MFCC features for emotion recognition; (2) the proposed hybrid emotion recognition system using both spectral and prosodic features yields the relative recognition error reduction rate of 17.0% over the traditional recognition systems using only the spectral features, and 62.3% over those using only the prosodic features.

収録刊行物

• IEICE Transactions on Information and Systems

  IEICE Transactions on Information and Systems E93-D (10), 2813-2821, 2010

  一般社団法人 電子情報通信学会

キーワード

• speech emotion recognition
• non-uniform subband processing
• spectral feature
• prosodic feature

詳細情報

• CRID: 1390001204379551488
• NII論文ID: 10027641285
• NII書誌ID: AA10826272
• DOI: 10.1587/transinf.e93.d.2813
• ISSN: 17451361
• ISSN: 09168532
• Web Site: http://hdl.handle.net/10119/9950
• Web Site: http://www.jstage.jst.go.jp/article/transinf/E93.D/10/E93.D_10_2813/_pdf
• 本文言語コード: en
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