Dimension Reduction of the Modulation Spectrogram for Speaker Verification.
Tomi Kinnunen, Kong-Aik Lee and Haizhou Li
Abstract
A so-called modulation spectrogram is obtained from the conventional speech spectrogram by short-term spectral analysis along the temporal trajectories of the frequency bins. In its original definition, the modulation spectrogram is a high-dimensional representation and it is not clear how to extract features from it. In this paper, we define a low-dimensional feature which captures the shape of the modulation spectra. The recognition accuracy of the modulation spectrogram based classifier is improved from our previous result of EER=25.1% to EER=17.4% on the NIST 2001 speaker recognition task.
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