Comparison of Classification Methods for Detecting Emotion from Mandarin Speech

Tsang-Long PAO; Yu-Te CHEN; Jun-Heng YEH

doi:10.1093/ietisy/e91-d.4.1074

Comparison of Classification Methods for Detecting Emotion from Mandarin Speech

Tsang-Long PAO, Yu-Te CHEN, Jun-Heng YEH

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It is said that technology comes out from humanity. What is humanity? The very definition of humanity is emotion. Emotion is the basis for all human expression and the underlying theme behind everything that is done, said, thought or imagined. Making computers being able to perceive and respond to human emotion, the human-computer interaction will be more natural. Several classifiers are adopted for automatically assigning an emotion category, such as anger, happiness or sadness, to a speech utterance. These classifiers were designed independently and tested on various emotional speech corpora, making it difficult to compare and evaluate their performance. In this paper, we first compared several popular classification methods and evaluated their performance by applying them to a Mandarin speech corpus consisting of five basic emotions, including anger, happiness, boredom, sadness and neutral. The extracted feature streams contain MFCC, LPCC, and LPC. The experimental results show that the proposed WD-MKNN classifier achieves an accuracy of 81.4% for the 5-class emotion recognition and outperforms other classification techniques, including KNN, MKNN, DW-KNN, LDA, QDA, GMM, HMM, SVM, and BPNN. Then, to verify the advantage of the proposed method, we compared these classifiers by applying them to another Mandarin expressive speech corpus consisting of two emotions. The experimental results still show that the proposed WD-MKNN outperforms others.

Publication: IEICE TRANSACTIONS on Information Vol.E91-D No.4 pp.1074-1081

Publication Date: 2008/04/01

Publicized

Online ISSN: 1745-1361

DOI: 10.1093/ietisy/e91-d.4.1074

Type of Manuscript: PAPER

Category: Human-computer Interaction

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Tsang-Long PAO, Yu-Te CHEN, Jun-Heng YEH, "Comparison of Classification Methods for Detecting Emotion from Mandarin Speech" in IEICE TRANSACTIONS on Information, vol. E91-D, no. 4, pp. 1074-1081, April 2008, doi: 10.1093/ietisy/e91-d.4.1074.
Abstract: It is said that technology comes out from humanity. What is humanity? The very definition of humanity is emotion. Emotion is the basis for all human expression and the underlying theme behind everything that is done, said, thought or imagined. Making computers being able to perceive and respond to human emotion, the human-computer interaction will be more natural. Several classifiers are adopted for automatically assigning an emotion category, such as anger, happiness or sadness, to a speech utterance. These classifiers were designed independently and tested on various emotional speech corpora, making it difficult to compare and evaluate their performance. In this paper, we first compared several popular classification methods and evaluated their performance by applying them to a Mandarin speech corpus consisting of five basic emotions, including anger, happiness, boredom, sadness and neutral. The extracted feature streams contain MFCC, LPCC, and LPC. The experimental results show that the proposed WD-MKNN classifier achieves an accuracy of 81.4% for the 5-class emotion recognition and outperforms other classification techniques, including KNN, MKNN, DW-KNN, LDA, QDA, GMM, HMM, SVM, and BPNN. Then, to verify the advantage of the proposed method, we compared these classifiers by applying them to another Mandarin expressive speech corpus consisting of two emotions. The experimental results still show that the proposed WD-MKNN outperforms others.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e91-d.4.1074/_p

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@ARTICLE{e91-d_4_1074,
author={Tsang-Long PAO, Yu-Te CHEN, Jun-Heng YEH, },
journal={IEICE TRANSACTIONS on Information},
title={Comparison of Classification Methods for Detecting Emotion from Mandarin Speech},
year={2008},
volume={E91-D},
number={4},
pages={1074-1081},
abstract={It is said that technology comes out from humanity. What is humanity? The very definition of humanity is emotion. Emotion is the basis for all human expression and the underlying theme behind everything that is done, said, thought or imagined. Making computers being able to perceive and respond to human emotion, the human-computer interaction will be more natural. Several classifiers are adopted for automatically assigning an emotion category, such as anger, happiness or sadness, to a speech utterance. These classifiers were designed independently and tested on various emotional speech corpora, making it difficult to compare and evaluate their performance. In this paper, we first compared several popular classification methods and evaluated their performance by applying them to a Mandarin speech corpus consisting of five basic emotions, including anger, happiness, boredom, sadness and neutral. The extracted feature streams contain MFCC, LPCC, and LPC. The experimental results show that the proposed WD-MKNN classifier achieves an accuracy of 81.4% for the 5-class emotion recognition and outperforms other classification techniques, including KNN, MKNN, DW-KNN, LDA, QDA, GMM, HMM, SVM, and BPNN. Then, to verify the advantage of the proposed method, we compared these classifiers by applying them to another Mandarin expressive speech corpus consisting of two emotions. The experimental results still show that the proposed WD-MKNN outperforms others.},
keywords={},
doi={10.1093/ietisy/e91-d.4.1074},
ISSN={1745-1361},
month={April},}

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TY - JOUR
TI - Comparison of Classification Methods for Detecting Emotion from Mandarin Speech
T2 - IEICE TRANSACTIONS on Information
SP - 1074
EP - 1081
AU - Tsang-Long PAO
AU - Yu-Te CHEN
AU - Jun-Heng YEH
PY - 2008
DO - 10.1093/ietisy/e91-d.4.1074
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E91-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2008
AB - It is said that technology comes out from humanity. What is humanity? The very definition of humanity is emotion. Emotion is the basis for all human expression and the underlying theme behind everything that is done, said, thought or imagined. Making computers being able to perceive and respond to human emotion, the human-computer interaction will be more natural. Several classifiers are adopted for automatically assigning an emotion category, such as anger, happiness or sadness, to a speech utterance. These classifiers were designed independently and tested on various emotional speech corpora, making it difficult to compare and evaluate their performance. In this paper, we first compared several popular classification methods and evaluated their performance by applying them to a Mandarin speech corpus consisting of five basic emotions, including anger, happiness, boredom, sadness and neutral. The extracted feature streams contain MFCC, LPCC, and LPC. The experimental results show that the proposed WD-MKNN classifier achieves an accuracy of 81.4% for the 5-class emotion recognition and outperforms other classification techniques, including KNN, MKNN, DW-KNN, LDA, QDA, GMM, HMM, SVM, and BPNN. Then, to verify the advantage of the proposed method, we compared these classifiers by applying them to another Mandarin expressive speech corpus consisting of two emotions. The experimental results still show that the proposed WD-MKNN outperforms others.
ER -