NDLI: A new score normalization for text-independent speaker verification

Content Provider	IEEE Xplore Digital Library
Author	Hongke Ning Zou, Y.X. Xuyan Hu
Copyright Year	2014
Description	Author affiliation: Sch. of ECE, Peking Univ., Shenzhen, China (Hongke Ning; Zou, Y.X.; Xuyan Hu)
Abstract	In iVector-based speaker verification system, the claimed speaker was verified if the similarity between the iVector of the tested utterance (iVector-ts) and the iVector of the claimed speaker (iVector-cs) is smaller than a fixed threshold. The commonly used method to measure the similarity between the iVector-ts and iVector-cs is the cosine similarity scoring method. To further improve the performance of the speaker verification system when the training data is insufficient, a new scoring method termed as ratio normalization (Rnorm) scoring method is proposed, where the similarity between iVector-ts and iVector-cs is normalized by the dissimilarity between the tested speaker model and the universal background model (UBM). Preliminary experimental results with Timit database and self-built database show that our proposed Rnorm scoring method is able to reduce the equal error rate (EER) of the iVector-based TIV speaker verification system compared with that of using conventional cosine similarity scoring method.
Starting Page	636
Ending Page	639
File Size	657244
Page Count	4
File Format	PDF
ISBN	9781479946129
ISSN	21653577
DOI	10.1109/ICDSP.2014.6900743
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speech Computational modeling Databases Cascading style sheets Digital signal processing Training Conferences ratio normalization cosine similarity scoring iVector-based speaker verification TIMIT
Content Type	Text
Resource Type	Article

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