Arbitrary Discrete Fourier Analysis and Its Application in Replayed Speech Detection

Author:

Shih-Kuang Lee

Keyword:

Electrical Engineering and Systems Science, Audio and Speech Processing, Audio and Speech Processing (eess.AS), Signal Processing (eess.SP)

journal:

date:

2024-03-02 00:00:00

Abstract

In this paper, a signal analysis concept is derived when revisiting how a specific frequency component in spectrum is analyzed in Fourier analysis. Three signal analysis methods are then developed based on the derived concept, namely Arbitrary Discrete Fourier Analysis (ADFA), Mel-scale Discrete Fourier Analysis (MDFA), and constant Q Analysis (CQA). I validate the effectiveness of these three signal analysis methods by testing their performance on a replayed speech detection benchmark (i.e., the ASVspoof 2019 Physical Access) along with a state-of-the-art model. Experimental results show that the performance of these three signal analysis methods is comparable to the best reported systems. At the same time, it is show that the computation time of the developed method CQA is much shorter than the convention method constant Q Transform, which is commonly used in spoofed and fake speech detection and music processing.

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