Contrasting the Effects of Different Frequency Bands on Speaker and Accent Identification

This letter presents an experimental study investigating the effect of frequency sub-bands on regional accent identification (AID) and speaker identification (SID) performance on the ABI-1 corpus. The AID and SID systems are based on Gaussian mixture modeling. The SID experiments show up to 100% acc...

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Bibliographic Details
Published in:IEEE signal processing letters 2012-12, Vol.19 (12), p.829-832
Main Authors: Safavi, S., Hanani, A., Russell, M., Jancovic, P., Carey, M. J.
Format: Article
Language:English
Subjects:
ABI-1
accent identification
Accuracy
Adaptation models
Band pass filters
Bandwidth
frequency region
Gaussian mixture model
Hidden Markov models
intersession variability compensation
speaker identification
Speech
sub-band
Training
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Summary:This letter presents an experimental study investigating the effect of frequency sub-bands on regional accent identification (AID) and speaker identification (SID) performance on the ABI-1 corpus. The AID and SID systems are based on Gaussian mixture modeling. The SID experiments show up to 100% accuracy when using the full 11.025 kHz bandwidth. The best AID performance of 60.34% is obtained when using band-pass filtered (0.23-3.4 kHz) speech. The experiments using isolated narrow sub-bands show that the regions (0-0.77 kHz) and (3.40-11.02 kHz) are the most useful for SID, while those in the region (0.34-3.44 kHz) are best for AID. AID experiments are also performed with intersession variability compensation, which provides the biggest performance gain in the (2.23-5.25 kHz) region.
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2012.2221697