Time-Frequency transformation and spectral representations of audio signals are commonly used in various machine learning applications. Typically the Mel-Spectrogram is used to create the input features to the network justified by the Mel scale’s human auditory system basis. In this paper, we compare several spectral features in a gender detection speech model comparing their performance and showing that the Mel-Spectrogram is not always the best choice for input features.

Authors: Vines, Greg; Nemer, Elias
Affiliations: San Diego, CA, USA; San Diego, CA, USA;(See document for exact affiliation information.)
AES Convention: 153 (October 2022) Paper Number: 10634
Publication Date: October 19, 2022 Import into BibTeX
Subject: Applications in Audio
Permalink: https://www.aes.org/e-lib/browse.cfm?elib=21963

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