Assessing vowel quality for singing evaluation

Abstract

The proper pronunciation of lyrics is an important component of vocal music. While automatic vowel classification has been widely studied for speech, a separate investigation of the methods is needed for singing due to the differences in acoustic properties between sung and spoken vowels. Acoustic features combining spectrum envelope and pitch are used with classifiers trained on sung vowels for classification of test vowels segmented from the audio of solo singing. Two different classifiers are tested, viz., Gaussian Mixture Models (GMM) and Linear Regression, and observed to perform well on both male and female sung vowels.