CASIA OpenIR  > 数字内容技术与服务研究中心  > 听觉模型与认知计算
AN INVESTIGATION OF SUMMED-CHANNEL SPEAKER RECOGNITION WITH MULTI-SESSION ENROLLMENT
Shanshan, Zhang; Ce, Zhang; Rong, Zheng; Xu, Bo; Shanshan,Zhang
2014
Conference Name2014 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
Source PublicationIEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Conference Date2014
Conference PlaceFlorence
Abstract
; This paper describes a general framework of speaker recognition
on summed-channel condition for both enrolling and test data. We
present several methods for clustering the target speaker who is
involved in multiple summed-channel enrolling excerpts. In our
approach, each excerpt is segmented separately by a speaker diarization
system as the first stage. Then segments belonging to the
same speaker are clustered to train the target speaker model, and
speaker verification is applied finally. We propose several effective
objective functions to measure the purity of clustered segments
in multi-session enrollment. Different confidence measures for
summed-channel scoring are also presented. We report experimental
results on female part in the NIST 2008 speaker recognition
evaluation data, which show that our approach applied on summedchannel
condition loses only 1% of the performance measured by
equal error rates (EER) compared to the two-channel condition.
KeywordSpeaker Recognition Summed-channel Speaker Clustering Multi-session
Indexed ByEI
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/11804
Collection数字内容技术与服务研究中心_听觉模型与认知计算
Corresponding AuthorShanshan,Zhang
AffiliationInteractive Digital Media Technology Research Center Institute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Shanshan, Zhang,Ce, Zhang,Rong, Zheng,et al. AN INVESTIGATION OF SUMMED-CHANNEL SPEAKER RECOGNITION WITH MULTI-SESSION ENROLLMENT[C],2014.
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