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Measuring Correlation between Mental Fatigues and Speech Features

정신피로와 음성특징과의 상관관계 측정

  • Received : 2014.05.13
  • Accepted : 2014.06.20
  • Published : 2014.06.30

Abstract

This paper deals with how mental fatigue has an effect on human voice. For this a monotonous task to increase the feeling of the fatigue and a set of subjective questionnaire for rating the fatigue were designed. From the experiments the designed task was proven to be monotonous based on the results of the questionnaire responses. To investigate a statistical relationship between speech features extracted from the collected speech data and fatigue, the T test for two-related-samples was used. Statistical analysis shows that speech parameters deeply related to the fatigue are the first formant bandwidth, Jitter, H1-H2, cepstral peak prominence, and harmonics-to-noise ratio. According to the experimental results, it can be seen that voice is changed to be breathy as mental fatigue proceeds.

Keywords

References

  1. Choi, E. S., Song, M. S. (2003). Concept analysis : Fatigue. Journal of Korean Academy of Women's Health Nursing, Vol. 9, No. 1, 61-69. (최의순, 송민선 (2003). 피로의 개념 분석. 여성건강간호학회지, 9권 1호, 61-69.)
  2. Yi, C. M., Ko, H. W., Yun, Y. H. (2000). The study on Korean-version-questionnaire for measurement of mental fatigue during monotonous task. Proc. Spring Conf. the Korean Society for Emotion & Sensibility, 195-202. (이창미, 고한우, 윤용현 (2000). 단조작업시 정신피로도 측정을 위한 한국어판 질문지에 관한 연구. 한국감성과학회 춘계학술대회 논문집, 195-202.)
  3. Tylee, A., Gandhi, P. (2005). The importance of somatic symptoms in depression in primary care. Primary Care Companion J. Clinic Psychiatry, Vol. 7, 167-176. https://doi.org/10.4088/PCC.v07n0405
  4. Lee, M. S., Joe, S. H. (2007). Biological aspects of fatigue. Korean J. Psychosomatic Medicine, Vol. 15, No. 2, 65-72. (이문수, 조숙행 (2007). 피로의 생물학적 측면, 정신신체의학, 15권 2호, 65-72.)
  5. Yun, Y. H., Ko, H. W., Kim, D. Y., Lee, C. M. (1999). Assesment of mental fatigue during monotonous task. Proc. Autumn Conf. the Korean Society for Emotion & Sensibility, 222-226. (윤용현, 고한우, 김동윤, 이창미 (1999). 단조작업에 의한 정신피로의 평가 - 생리신호를 중심으로, 감성공학 추계학술대회 논문집, 222-226.)
  6. Ko, H. W., Yun, Y. H., Kim, D. Y., Lee, C. M. (2000). Measurement and assessment of mental fatigue using biosignals during monotonous task. Korean Journal of the Science of Emotion & Sensibility, Vol. 3, No. 1, 1-6. (고한우, 윤용현, 김동윤, 이창미 (2000). 생리신호를 사용한 단조 작업 수행시 정신피로도의 측정과 평가, 한국감성과학회지, 3권 1호, 1-6.)
  7. Song, S. K., Kim, J. Y., Jang, J. S., Kwon, C. H. (2013). A validity study on measurement of mental fatigue using speech technology. The Phonetics and Speech Sciences, Vol. 5, No. 1, 3-10. (송승규, 김종열, 장준수, 권철홍 (2013). 음성기술을 이용한 정신피로 측정에 관한 타당성 연구. 한국음성학회, 말소리와 음성과학, 5권 1호, 3-10.) https://doi.org/10.13064/KSSS.2013.5.1.003
  8. Klatt, D. H., Klatt, L. C. (1990). Analysis, synthesis, and perception of voice quality variations among female and male speakers. J. of the Acoustical Society of America, Vol. 87, No. 2, 820-857. https://doi.org/10.1121/1.398894
  9. Hwang, Y. S., Seong, C. J. (2008). Comparative study on the acoustic characteristics of the Korean vowel /a/ before and after LMS. Malsori, Vol. 67, 33-60. (황연신, 성철재 (2008). 후두미세수술 전후 /아/의 음향적 특성 비교. 대한음성학회, 말소리 67호, 33-60.)
  10. Dekrom, G. (1995). Some spectral correlates of pathological breathy and rough voice quality for different types of vowel fragments. J. of Speech Hearing Res., Vol. 38, 794-811. https://doi.org/10.1044/jshr.3804.794
  11. Mathew, M. M., Bhat, J. S. (2009). Soft phonation index - a sensitive parameter?. Indian J. of Otolaryngology Head Neck Surg., Vol. 61, 127-130. https://doi.org/10.1007/s12070-009-0050-4
  12. Hillenbrand, J., Houde, R. A. (1996). Acoustic correlates of breathy vocal quality: dysphonic voices and continuous speech. J. of Speech and Hearing Research, Vol. 39, 311-321. https://doi.org/10.1044/jshr.3902.311
  13. Praat. (2014). Phonetic Sciences, Univ. of Amsterdam, http://www.fon.hum.uva.nl/praat/.
  14. MDVP. (2014). KayPentax, http://www.kayelemetrics.com.
  15. VoiceSauce. (2014). A program for voice analysis, UCLA, http://www.seas.ucla.edu/spapl/voicesauce/.
  16. Kim, J. I., Kwon, C. H., (2014). Qualitative classification of voice quality of normal speech and derivation of its correlation with speech features. The Phonetics and Speech Sciences, Vol. 6, No. 1, 71-76. (김정인, 권철홍 (2014). 정상 음성의 목소리 특성의 정성적 분류와 음성 특징과의 상관관계 도출. 한국음성학회, 말소리와 음성과학, 6권 1호, 71-76.) https://doi.org/10.13064/KSSS.2014.6.1.071
  17. Seo, E. H. (2010). Statistical analysis using SPSS 18.0. Free Academy, 403-415. (서의훈 (2010). SPSS 18.0을 이용한 통계분석, 자유아카데미, 403-415.)
  18. IBM SPSS Statistics. (2014). SPSS Korea, http://www.spss.co.kr.
  19. Park, H. S. (2007). An acoustic study of phonation types in vowels following consonant clusters in Korean. Malsori, Vol. 64, 53-76. (박한상 (2007). 한국어 자음군의 후행모음에 나타난 발성유형의 음향음성학적 연구. 대한음성학회, 말소리 64호, 53-76.)