목소리 특성의 청취 평가에 기초한 사상체질과 음성 특징의 상관관계 분석
Analysis of the Relationship Between Sasang Constitutional Groups and Speech Features Based on a Listening Evaluation of Voice Characteristics
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초록
Sasang constitution experts utilize voice characteristics as an auxiliary measure for deciding a person's constitutional group. This study aims at establishing a relationship between speech features and the constitutional groups by subjective listening evaluation of voice characteristics. A speech database of 841 speakers whose constitutional groups have been already diagnosed by Sasang constitution experts was constructed. Speech features related to speech source and vocal tract filter were extracted from five vowels and one sentence. Statistically significant speech features for classifying the groups were analyzed using SPSS. The features contributed to constitution classification were speaking rate, Energy, A1, A2, A3, H1, H2, H4, CPP for males in their 20s, F0_mean, CPP, SPI, HNR, Shimmer, Energy, A1, A2, A3, H1, H2, H4 for females in their 20s, Energy,A1, A2, A3, H1, H2, H4, CPP for male in the 60s, and Jitter, HNR, CPP, SPI for females in their 60s. Experimental results show that speech technology is useful in classifying constitutional groups.
Abstract
Sasang constitution experts utilize voice characteristics as an auxiliary measure for deciding a person's constitutional group. This study aims at establishing a relationship between speech features and the constitutional groups by subjective listening evaluation of voice characteristics. A speech database of 841 speakers whose constitutional groups have been already diagnosed by Sasang constitution experts was constructed. Speech features related to speech source and vocal tract filter were extracted from five vowels and one sentence. Statistically significant speech features for classifying the groups were analyzed using SPSS. The features contributed to constitution classification were speaking rate, Energy, A1, A2, A3, H1, H2, H4, CPP for males in their 20s, F0_mean, CPP, SPI, HNR, Shimmer, Energy, A1, A2, A3, H1, H2, H4 for females in their 20s, Energy,A1, A2, A3, H1, H2, H4, CPP for male in the 60s, and Jitter, HNR, CPP, SPI for females in their 60s. Experimental results show that speech technology is useful in classifying constitutional groups.
참고문헌 (13)
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