Yıl 2018, Cilt , Sayı 14, Sayfalar 241 - 244 2018-12-31

Investigation of the Relation between Emotional State and Acoustic Parameters in the Context of Language
Investigation of the Relation between Emotional State and Acoustic Parameters in the Context of Language

Turgut Özseven [1]

14 36

Acoustic analysis is the most basic method used for speech emotion recognition. Speech records are digitized by signal processing methods, and various acoustic features of speech are obtained by acoustic analysis methods. The relationship between acoustic features and emotion has been investigated in many studies. However, studies have mostly focused on emotion recognition success or the effects of emotions on acoustic features. The effect of spoken language on speech emotion recognition has been investigated in a limited number. The purpose of this study is to investigate the variability of the relationship between acoustic features and emotions according to the spoken language. For this purpose, three emotions (anger, fear and neutral) of three different spoken languages (English, German and Italian) were used. In these data sets, the change in acoustic features according to spoken language was investigated statistically. According to the results obtained, the effect of anger on the acoustic features does not change according to the spoken language. For fear, change in spoken language shows a high similarity in Italian and German, but low similarity in English.

Acoustic analysis is the most basic method used for speech emotion recognition. Speech records are digitized by signal processing methods, and various acoustic features of speech are obtained by acoustic analysis methods. The relationship between acoustic features and emotion has been investigated in many studies. However, studies have mostly focused on emotion recognition success or the effects of emotions on acoustic features. The effect of spoken language on speech emotion recognition has been investigated in a limited number. The purpose of this study is to investigate the variability of the relationship between acoustic features and emotions according to the spoken language. For this purpose, three emotions (anger, fear and neutral) of three different spoken languages (English, German and Italian) were used. In these data sets, the change in acoustic features according to spoken language was investigated statistically. According to the results obtained, the effect of anger on the acoustic features does not change according to the spoken language. For fear, change in spoken language shows a high similarity in Italian and German, but low similarity in English.

  • [1] B. Zupan, D. Neumann, D. R. Babbage, and B. Willer, ‘The importance of vocal affect to bimodal processing of emotion: implications for individuals with traumatic brain injury’, J. Commun. Disord., vol. 42, no. 1, pp. 1–17, 2009.
  • [2] F. Burkhardt, A. Paeschke, M. Rolfes, W. F. Sendlmeier, and B. Weiss, ‘A database of German emotional speech.’, in Interspeech, 2005, vol. 5, pp. 1517–1520.
  • [3] G. Costantini, I. Iaderola, A. Paoloni, and M. Todisco, ‘EMOVO Corpus: an Italian Emotional Speech Database.’, in LREC, 2014, pp. 3501–3504.
  • [4] P. Jackson, S. Haq, and J. D. Edge, ‘Audio-Visual Feature Selection and Reduction for Emotion Classification’, in In Proc. Int’l Conf. on Auditory-Visual Speech Processing, 2008, pp. 185–190.
  • [5] J. H. Hansen, S. E. Bou-Ghazale, R. Sarikaya, and B. Pellom, ‘Getting started with SUSAS: a speech under simulated and actual stress database.’, in Eurospeech, 1997, vol. 97, pp. 1743–46.
  • [6] P. Boersma and D. Weenink, Praat: doing phonetics by computer [Computer program], Version 5.1. 44. 2010.
  • [7] F. Eyben, M. Wöllmer, and B. Schuller, ‘Opensmile: the munich versatile and fast open-source audio feature extractor’, in Proceedings of the international conference on Multimedia, 2010, pp. 1459–1462.
  • [8] W. Tarng, Y.-Y. Chen, C.-L. Li, K.-R. Hsie, and M. Chen, ‘Applications of support vector machines on smart phone systems for emotional speech recognition’, World Acad. Sci. Eng. Technol., vol. 72, pp. 106–113, 2010.
  • [9] M. C. Sezgin, B. Gunsel, and G. K. Kurt, ‘Perceptual audio features for emotion detection’, EURASIP J. Audio Speech Music Process., vol. 2012, no. 1, pp. 1–21, 2012.
  • [10] M. Grimm, K. Kroschel, E. Mower, and S. Narayanan, ‘Primitives-based evaluation and estimation of emotions in speech’, Speech Commun., vol. 49, no. 10–11, pp. 787–800, Oct. 2007.
  • [11] D. D. Joshi and M. B. Zalte, Recognition of Emotion from Marathi Speech Using MFCC and DWT Algorithms. IJACECT, 2013.
  • [12] S. Sarıca, ‘Ses Analizinde Kullanılan Akustik Parametreler’, Tıpta Uzmanlık Tezi, Kahramanmaraş Sütçü İmam Üniversitesi Tıp Fakültesi, Kahramanmaraş, 2012.
  • [13] K. M. Okur E., ‘CSL ve Dr. Speech ile ölçülen temel frekans ve pertürbasyon değerlerinin karşılaştırılması’, KBB Ihtis. Derg., vol. 8, pp. 152–157, 2001.
  • [14] M. Farrus and J. Hernando, ‘Using jitter and shimmer in speaker verification’, Signal Process. IET, vol. 3, no. 4, pp. 247–257, 2009.
  • [15] O. Deshmukh, C. Y. Espy-Wilson, A. Salomon, and J. Singh, ‘Use of temporal information: Detection of periodicity, aperiodicity, and pitch in speech’, Speech Audio Process. IEEE Trans. On, vol. 13, no. 5, pp. 776–786, 2005.
  • [16] Y. Karagöz, ‘Nonparametrik tekniklerin güç ve etkinlikleri’, Elektron. Sos. Bilim. Derg., vol. 9, no. 33, pp. 18–40, 2010.
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Orcid: 0000-0002-6325-461X
Yazar: Turgut Özseven (Sorumlu Yazar)
Ülke: Turkey


Bibtex @araştırma makalesi { ejosat448095, journal = {Avrupa Bilim ve Teknoloji Dergisi}, issn = {}, eissn = {2148-2683}, address = {Osman Sağdıç}, year = {2018}, volume = {}, pages = {241 - 244}, doi = {10.31590/ejosat.448095}, title = {Investigation of the Relation between Emotional State and Acoustic Parameters in the Context of Language}, key = {cite}, author = {Özseven, Turgut} }
APA Özseven, T . (2018). Investigation of the Relation between Emotional State and Acoustic Parameters in the Context of Language. Avrupa Bilim ve Teknoloji Dergisi, (14), 241-244. DOI: 10.31590/ejosat.448095
MLA Özseven, T . "Investigation of the Relation between Emotional State and Acoustic Parameters in the Context of Language". Avrupa Bilim ve Teknoloji Dergisi (2018): 241-244 <http://dergipark.gov.tr/ejosat/issue/40225/448095>
Chicago Özseven, T . "Investigation of the Relation between Emotional State and Acoustic Parameters in the Context of Language". Avrupa Bilim ve Teknoloji Dergisi (2018): 241-244
RIS TY - JOUR T1 - Investigation of the Relation between Emotional State and Acoustic Parameters in the Context of Language AU - Turgut Özseven Y1 - 2018 PY - 2018 N1 - doi: 10.31590/ejosat.448095 DO - 10.31590/ejosat.448095 T2 - Avrupa Bilim ve Teknoloji Dergisi JF - Journal JO - JOR SP - 241 EP - 244 VL - IS - 14 SN - -2148-2683 M3 - doi: 10.31590/ejosat.448095 UR - http://dx.doi.org/10.31590/ejosat.448095 Y2 - 2018 ER -
EndNote %0 Avrupa Bilim ve Teknoloji Dergisi Investigation of the Relation between Emotional State and Acoustic Parameters in the Context of Language %A Turgut Özseven %T Investigation of the Relation between Emotional State and Acoustic Parameters in the Context of Language %D 2018 %J Avrupa Bilim ve Teknoloji Dergisi %P -2148-2683 %V %N 14 %R doi: 10.31590/ejosat.448095 %U 10.31590/ejosat.448095
ISNAD Özseven, Turgut . "Investigation of the Relation between Emotional State and Acoustic Parameters in the Context of Language". Avrupa Bilim ve Teknoloji Dergisi / 14 (Aralık 2019): 241-244. http://dx.doi.org/10.31590/ejosat.448095