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.
Original language | English |
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Publication status | Published - Jan 2008 |
Externally published | Yes |
Event | Speaker and Language Recognition Workshop, Odyssey 2008 - Stellenbosch, South Africa Duration: 21 Jan 2008 → 24 Jan 2008 |
Conference
Conference | Speaker and Language Recognition Workshop, Odyssey 2008 |
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Country/Territory | South Africa |
City | Stellenbosch |
Period | 21/01/08 → 24/01/08 |
Keywords
- Modulation spectrum
- Speaker recognition
- Spectro-temporal features
ASJC Scopus subject areas
- Human-Computer Interaction
- Software
- Signal Processing