영어 감정발화와 중립발화 간의 운율거리를 이용한 감정발화 분석
An analysis of emotional English utterances using the prosodic distance between emotional and neutral utterances
2
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
An analysis of emotional English utterances with 7 emotions (calm, happy, sad, angry, fearful, disgust, surprised) was conducted using the measurement of prosodic distance between 672 emotional and 48 neutral utterances. Applying the technique proposed in the automatic evaluation model of English pronunciation to the present study on emotional utterances, Euclidean distance measurement of 3 prosodic elements such as F0, intensity and duration extracted from emotional and neutral utterances was utilized. This paper, furthermore, extended the analytical methods to include Euclidean distance normalization, z-score and z-score normalization resulting in 4 groups of measurement schemes (sqrF0, sqrINT, sqrDUR; norsqrF0, norsqrINT, norsqrDUR; sqrzF0, sqrzINT, sqrzDUR; norsqrzF0, norsqrzINT, norsqrzDUR). All of the results from perceptual analysis and acoustical analysis of emotional utteances consistently indicated the greater effectiveness of norsqrF0, norsqrINT and norsqrDUR, among 4 groups of measurement schemes, which normalized the Euclidean measurement. The greatest acoustical change of prosodic information influenced by emotion was shown in the values of F0 followed by duration and intensity in descending order according to the effect size based on the estimation of distance between emotional utterances and neutral counterparts. Tukey Post Hoc test revealed 4 homogeneous subsets (calm<disgust, sad<happy, surprised<surprised, angry, fearful) statistically determined from the measurement of norsqrF0 and 3 homogeneous subsets (surprised, happy, fearful, sad, calm<calm, angry<angry, disgust) from norsqrDUR. Furthermore, the analysis of each of the 7 emotions showed that the present research outcome is in the same vein as the results of the previous study.
Abstract
An analysis of emotional English utterances with 7 emotions (calm, happy, sad, angry, fearful, disgust, surprised) was conducted using the measurement of prosodic distance between 672 emotional and 48 neutral utterances. Applying the technique proposed in the automatic evaluation model of English pronunciation to the present study on emotional utterances, Euclidean distance measurement of 3 prosodic elements such as F0, intensity and duration extracted from emotional and neutral utterances was utilized. This paper, furthermore, extended the analytical methods to include Euclidean distance normalization, z-score and z-score normalization resulting in 4 groups of measurement schemes (sqrF0, sqrINT, sqrDUR; norsqrF0, norsqrINT, norsqrDUR; sqrzF0, sqrzINT, sqrzDUR; norsqrzF0, norsqrzINT, norsqrzDUR). All of the results from perceptual analysis and acoustical analysis of emotional utteances consistently indicated the greater effectiveness of norsqrF0, norsqrINT and norsqrDUR, among 4 groups of measurement schemes, which normalized the Euclidean measurement. The greatest acoustical change of prosodic information influenced by emotion was shown in the values of F0 followed by duration and intensity in descending order according to the effect size based on the estimation of distance between emotional utterances and neutral counterparts. Tukey Post Hoc test revealed 4 homogeneous subsets (calm<disgust, sad<happy, surprised<surprised, angry, fearful) statistically determined from the measurement of norsqrF0 and 3 homogeneous subsets (surprised, happy, fearful, sad, calm<calm, angry<angry, disgust) from norsqrDUR. Furthermore, the analysis of each of the 7 emotions showed that the present research outcome is in the same vein as the results of the previous study.
참고문헌 (18)
- Bachorowski, J., "Vocal expression of emotion : Acoustic properties of speech are associated with emotional intensity and context", Psychological Science, 6(4), pp.219~224 (1995)
- (2020)[URL]
- Breazeal, C., "Emotion and sociable humanoid robots", International Journal of Human-Computer Studies, 59(1), pp.119~155 (2003)
- Generating expression in synthesized speech (Technical report), "Cahn, J.", MIT Media Lab, ~ (1990)
- Carlson, R., "Experiments with emotive speech: Acted utterances and synthesized replicas", Proceedings of the International Conference on Spoken Language Processing (ICSLP-92), pp.671~674 (1992)
- Kitahara, Y., "Prosodic control to express emotions for man-machine interaction", IEICE Transactions on Fundamentals of Electronics : Communications and Computer Sciences, 75(2), pp.155~163 (1992)
- Kitayama, S., "Word and voice : spontaneous attention to emotional utterances in two languages", Cognition and Emotion, 16(1), pp.29~59 (2002)
- Livingstone, S. R., "The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS): A dynamic, multimodal set of facial and vocal expressions in North American english", PLOS ONE, 13(5), pp.e0196391~ (2018)
- Mozziconacci, S., "Speech variability and emotion: Production and perception", 박사, pp.1998
- Paulmann, S., "Neurobiology of language", pp.1109~1120 (2016), Elsevier
- Pell, M., "Factors in the recognition of vocally expressed emotions : A comparison of our languages", Journal of Phonetics, 37(4), pp.417~435 (2009)
- Thompson, W. F., "Handbook of music and emotion: Theory, research, applications", pp.755~791 (2009), Oxford University Press
- Vroomen, J., "Duration and intonation in emotional speech", Proceedings of the 3rd European Conference on Speech Communication and Technology. Eurospeech-93, pp.577~580 (1993)
- Williams, C., "Emotions and speech: Some acoustical correlates", The Journal of the Acoustical Society of America, 52(4B), pp.1238~1250 (1972)
- 이서배, "한국어 감정 음성에서 모멜로 추출한 피치 곡선 연구", 언어과학, 25(3), pp.191~209 (2018), 한국언어과학회[DOI]
- 윤규철, "Building a Sentential Model for Automatic Prosody Evaluation", 말소리와 음성과학, 1(4), pp.47~59 (2009), 한국음성학회
- 윤규철, "Synthesis and Evaluation of Prosodically Exaggerated Utterances", 말소리와 음성과학, 1(3), pp.73~85 (2009), 한국음성학회
- 윤규철, "영어 발음 평가 모델을 활용한 수동 평가자 연구", 말소리와 음성과학, 5(4), pp.109~119 (2013), 한국음성학회[DOI]