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Title: Automatic Classification of Voice Quality: Comparing Regression Models and Hidden Markov Models
Authors: Wester, Mirjam
Issue Date: 1998
Citation: Proceedings of VOICEDATA98, symposium on databases in voice quality research and education, pp. 92-97, Utrecht, 1998.
Publisher: Utrecht Institute of Linguistics OTS
Abstract: In this paper, two methods for automatically classifying voice quality are compared: regression analysis and hidden Markov models (HMMs). The findings of this research show that HMMs can be used to classify voice quality. The HMMs performed better than the regression models in classifying breathiness and overall degree of deviance, and the two methods showed similar results on the roughness scale. However, the results are not spectacular. This is mainly due to the type of material that was available and the number of listeners who assessed the material. Nonetheless, I argue in this paper that these findings are interesting because they are a promising step towards developing a system for classifying voice quality.
Appears in Collections:CSTR publications

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