Phonetics and Speech Sciences (말소리와 음성과학)

Korean Society of Speech Sciences (한국음성학회)
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Correlation analysis of voice characteristics and speech feature parameters, and classification modeling using SVM algorithm

목소리 특성과 음성 특징 파라미터의 상관관계와 SVM을 이용한 특성 분류 모델링

  • Received : 2017.10.30
  • Accepted : 2017.12.15
  • Published : 2017.12.31
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Abstract

This study categorizes several voice characteristics by subjective listening assessment, and investigates correlation between voice characteristics and speech feature parameters. A model was developed to classify voice characteristics into the defined categories using SVM algorithm. To do this, we extracted various speech feature parameters from speech database for men in their 20s, and derived statistically significant parameters correlated with voice characteristics through ANOVA analysis. Then, these derived parameters were applied to the proposed SVM model. The experimental results showed that it is possible to obtain some speech feature parameters significantly correlated with the voice characteristics, and that the proposed model achieves the classification accuracies of 88.5% on average.

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References

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