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Comparative Study of Filter Characteristics as Statistical Vocal Correlates of Clinical Psychiatric State in Human
Abstract:Acoustical properties of speech have been shown to be related to mental states of speaker with symptoms: depression and remission. This paper describes way to address the issue of distinguishing depressed patients from remitted subjects based on measureable acoustics change of their spoken sound. The vocal-tract related frequency characteristics of speech samples from female remitted and depressed patients were analyzed via speech processing techniques and consequently, evaluated statistically by cross-validation with Support Vector Machine. Our results comparatively show the classifier's performance with effectively correct separation of 93% determined from testing with the subjectbased feature model and 88% from the frame-based model based on the same speech samples collected from hospital visiting interview sessions between patients and psychiatrists.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1082791Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1225
 M. Hamilton, "A rating scale for depression", Journal of Neurology, Neurosurgery and Psychiatry, Vol. 23, pp. 56-62, 1960
 France, D.J., et al., "Acoustical properties of speech as indicators of depression and suicide", IEEE transactions on BME, 2000. 47:p 829-837.
 Ozdas, A., et al., "Analysis of Vocal Tract Characteristics for Near-term Suicidal Risk Assessment", Meth.Info.in Medicine, 2004. 43: p. 36-38.
 Ozdas, A., et al., "Investigation of Vocal Jitter and Glottal Flow Spectrum as Possible Cues for Depression and Near-Term Suicidal Risk", IEEE Transactions on BME, 2004. 51: p. 1530-1540.
 T. Yingthawornsuk, H. Kaymaz Keskinpala, D. France, D. M. Wilkes, R. G. Shiavi, R.M. Salomon, "Objective Estimation of Suicidal Risk using Vocal Output Characteristics", International Conference on Spoken Language Processing (ICSLP-Interspeech 2006), 2006, pp. 649-652.
 T. Yingthawornsuk, et al., "Direct Acuostic Feature using Iterative EM Algorithm and Spectral Energy for Classifying Suicidal Risk", Interspeech 2007, Antwerp, Belguim.
 F. Tolkmitt, H. Helfrich, R. Standke, K.R. Scherer, "Vocal Indicators of Psychiatric Treatment Effects in Depressives and Schizophrenics", J. Communication Disorders, Vol.15, pp.209-222, 1982.
 G. Fairbanks, Voice and Articulation Drillbook. Harper &Row, New York, 1960.
 A.T. Beck, st al., "An inventory for measuring depression", Arch Gen Psychiatry, 1961. 4:p. 561-571
 Dempster, A.P., et al., "Maximum likelihood from incomplete data via the EM algorithm", J. Royal Stat. Soc. Series B, 39:1-38, 1977.
 V.N. Vapnik, The Natural of Statistical Learning Theory. 2nd ed., Springer Verlag (New York), Dec 1999
 C. Cortes and V.N. Vapnik , "Support vector networks", Machine Learning, vol.20, pp. 1-25, 1995.
 A.J. Richard, Applied Multivariate Statistical Analysis. 3th ed., Prentice hall, New Jersey, 1992