10th Annual Conference of the International Speech Communication Association

Brighton, United Kingdom
September 6-10, 2009

Text-Independent Speaker Verification Using Rank Threshold in Large Number of Speaker Models

Haruka Okamoto (1), Satoru Tsuge (2), Amira Abdelwahab (1), Masafumi Nishida (3), Yasuo Horiuchi (1), Shingo Kuroiwa (1)

(1) Chiba University, Japan
(2) University of Tokushima, Japan
(3) Doshisha University, Japan

In this paper, we propose a novel speaker verification method which determines whether a claimer is accepted or rejected by the rank of the claimer in a large number of speaker models instead of score normalization, such as T-norm and Z-norm. The method has advantages over the standard T-norm in speaker verification accuracy. However, it needs much computation time as well as T-norm that needs calculating likelihoods for many cohort models. Hence, we also discuss the speed-up using the method that selects cohort subset for each target speaker in the training stage. This data driven approach can significantly reduce computation resulting in faster speaker verification decision. We conducted text-independent speaker verification experiments using large-scale Japanese speaker recognition evaluation corpus constructed by National Research Institute of Police Science. As a result, the proposed method achieved an equal error rate of 2.2%, while T-norm obtained 2.7%.

Full Paper

Bibliographic reference.  Okamoto, Haruka / Tsuge, Satoru / Abdelwahab, Amira / Nishida, Masafumi / Horiuchi, Yasuo / Kuroiwa, Shingo (2009): "Text-independent speaker verification using rank threshold in large number of speaker models", In INTERSPEECH-2009, 2367-2370.