International Journal of Music Science, Technology and Art

...an essential requirement for anyone who needs to keep up to date with new developments of music concepts throughout the world.


Archive

journal banner

IJMSTA - Vol. 3 - Issue 1 - January 2021
ISSN 2612-2146
Pages: 9

A Pilot Study for Algorithmic Diction Detection for Use by Singers and Vocal Teachers

Authors: Bhawna Rathi, Timothy Y. Hsu
Categories: Journal

Abstract - This paper introduces an algorithmic signal processing method to quantify vocal diction using audio files that can potentially assist singers and teachers. Clear diction and pronunciation in singing is important for a variety of reasons and should be exercised alongside the development of voice. In order to convey a clear verbal message, strong diction is needed. To accomplish this goal of diction detection, the interpretation of the consonants is of prime significance. The proposed algorithm works with features such as zero crossing rate, spectral spread, spectral flux and spectral centroid. In this paper, we offer a proposed framework and algorithm of diction detection using modern applicable audio features and extraction techniques. Future approach for analysis of diction is also defined.

Keywords: Diction, Signal processing, Vocal technologies, Detection, Audio feature extraction


Download paper


About this paper
 

Cite this paper as:
Rathi, B., Hsu, T.Y.: A Pilot Study for Algorithmic Diction Detection for Use by Singers and Vocal Teachers. IJMSTA. 2021 Jan 7; 3 (1): 24-32.

DOI: https://doi.org/10.48293/IJMSTA-73

Resources