2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
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Paper Detail

Paper IDSPE-8.6
Paper Title IMPROVING SPEAKER VERIFICATION IN REVERBERANT ENVIRONMENTS
Authors Xiao Chen, Stephen Zahorian, Binghamton University, United States
SessionSPE-8: Speaker Recognition 2: Channel and Domain Robustness
LocationGather.Town
Session Time:Tuesday, 08 June, 14:00 - 14:45
Presentation Time:Tuesday, 08 June, 14:00 - 14:45
Presentation Poster
Topic Speech Processing: [SPE-SPKR] Speaker Recognition and Characterization
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Speaker verification technology has been successfully adopted and integrated into many applications. However, most of these applications require a microphone located near the talker. For the case of distant microphones, speech signals are corrupted by reverberations caused by the large speaker to microphone distance. In this paper, we first introduce a new feature set that gives more details in the frequency dimension in the 2-D time-frequency space used to represent speech. These features are computed using two sets of basis vectors, both of which are applied directly to the amplitude compressed FFT spectrum. One set of basis vectors accounts for the spectral envelope while the second set accounts for pitch. Those features are used to train a CNN, with the goal of reducing the negative effects of reverberation. The proposed frontend is shown to be robust for speaker verification in reverberant environments.