Abstract
Many adjectives have been used to describe voice characteristics, yet it is challenging to define sound style precisely using quantitative measure. In this paper, we attempt to tackle the voice style classification problem based on techniques designed for speaker recognition. Specifically, we employ i-vector, a widely adopted feature in speaker identification, and support vector machine (SVM), for style classification. In order to verify the reliability of i-vector, we conduct pilot study, including noise sensitivity, minimum voice duration, and mimicry style test. In this study, we define eight voice styles and collect appropriate voice data to process and verify our hypothesis through the experiment. The results indicate that i-vector can indeed be utilized to classify voice styles that are commonly perceived in daily life.
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Liao, WH., Kao, WT., Wu, YC. (2019). Analysis of Voice Styles Using i-Vector Features. In: Chang, CY., Lin, CC., Lin, HH. (eds) New Trends in Computer Technologies and Applications. ICS 2018. Communications in Computer and Information Science, vol 1013. Springer, Singapore. https://doi.org/10.1007/978-981-13-9190-3_70
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DOI: https://doi.org/10.1007/978-981-13-9190-3_70
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