Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/89625
Title: An investigation of spoofing speech detection under additive noise and reverberant conditions
Authors: Tian, Xiaohai
Wu, Zhizheng
Xiao, Xiong
Chng, Eng Siong
Li, Haizhou
Keywords: Spoofing Detection
Noisy Database
Engineering::Computer science and engineering
Issue Date: 2016
Source: Tian, X., Wu, Z., Xiao, X., Chng, E. S., & Li, H. (2016). An investigation of spoofing speech detection under additive noise and reverberant conditions. Interspeech 2016. doi:10.21437/Interspeech.2016-743
Abstract: Spoofing detection for automatic speaker verification (ASV), which is to discriminate between live and artificial speech, has received increasing attentions recently. However, the previous studies have been done on the clean data without significant noise. It is still not clear whether the spoofing detectors trained on clean speech can generalise well under noisy conditions. In this work, we perform an investigation of spoofing detection under additive noise and reverberant conditions. In particular, we consider five difference additive noises at three different signalto-noise ratios (SNR), and a reverberation noise with different reverberation time (RT). Our experimental results reveal that additive noises degrade the spoofing detectors trained on clean speech significantly. However, the reverberation does not hurt the performance too much.
URI: https://hdl.handle.net/10356/89625
http://hdl.handle.net/10220/50288
DOI: 10.21437/Interspeech.2016-743
Rights: © 2016 International Speech Communication Association (ISCA). All rights reserved. This paper was published in Interspeech 2016 and is made available with permission of International Speech Communication Association (ISCA).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Conference Papers
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