A neural network was trained and tested to provide automated classification of singing voices, both recognizing voice quality (amateur, semiprofessional, and professional) and voice type (bass, baritone, tenor, alto, mezzo-soprano, and soprano). Parameters related to singing were defined to form feature vectors. Single vowel samples for each singer were judged by six experts to establish a quality index. In a test based on a database of 2690 samples, 90% of the decisions were correct. These results show that it is possible to use neural networks to create an expert system to evaluate singing.

Authors: Zwan, Pawel; Kostek, Bozena
Affiliation: Gdansk University of Technology, Multimedia Systems Department, 80-952 Gdansk, Poland
JAES Volume 56 Issue 9 pp. 710-723; September 2008
Publication Date: October 10, 2008 Import into BibTeX
Permalink: https://www.aes.org/e-lib/browse.cfm?elib=14634

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