Speaker-Dependent Dictionary-Based Speech Enhancement for Text-Dependent Speaker Verification

Nicolai Bæk Thomsen, Dennis Alexander Lehmann Thomsen, Zheng-Hua Tan, Børge Lindberg, Søren Holdt Jensen


The problem of text-dependent speaker verification under noisy conditions is becoming ever more relevant, due to increased usage for authentication in real-world applications. Classical methods for noise reduction such as spectral subtraction and Wiener filtering introduce distortion and do not perform well in this setting. In this work we compare the performance of different noise reduction methods under different noise conditions in terms of speaker verification when the text is known and the system is trained on clean data (mis-matched conditions). We furthermore propose a new approach based on dictionary-based noise reduction and compare it to the baseline methods.


DOI: 10.21437/Interspeech.2016-763

Cite as

Thomsen, N.B., Thomsen, D.A.L., Tan, Z., Lindberg, B., Jensen, S.H. (2016) Speaker-Dependent Dictionary-Based Speech Enhancement for Text-Dependent Speaker Verification. Proc. Interspeech 2016, 1839-1843.

Bibtex
@inproceedings{Thomsen+2016,
author={Nicolai Bæk Thomsen and Dennis Alexander Lehmann Thomsen and Zheng-Hua Tan and Børge Lindberg and Søren Holdt Jensen},
title={Speaker-Dependent Dictionary-Based Speech Enhancement for Text-Dependent Speaker Verification},
year=2016,
booktitle={Interspeech 2016},
doi={10.21437/Interspeech.2016-763},
url={http://dx.doi.org/10.21437/Interspeech.2016-763},
pages={1839--1843}
}