NDLI: A fast two-level Speaker Identification method employing sparse representation and GMM-based methods

Content Provider	IEEE Xplore Digital Library
Author	Zeinali, H. Sameti, H. Khaki, H. Babaali, B.
Copyright Year	2012
Description	Author affiliation: Department of Electrical Engineering, Sharif University of Technology, Iran (Khaki, H.) \|\| Department of Computer Engineering, Sharif University of Technology, Iran (Zeinali, H.; Sameti, H.; Babaali, B.)
Abstract	In large population Speaker Identification (SI), computation time has become one of the most important issues in recent real time systems. Test computation time depends on the cost of likelihood computation between test features and registered speaker models. For real time application of speaker identification, system must identify an unknown speaker quickly. Hence the conventional SI methods cannot be used. In this paper, we propose a two-step method that utilizes two different identification methods. In the first step we use Nearest Neighbor method to decrease the search space. In the second step we use GMM-based SI methods to specify the target speaker. We achieved 3.5× speed-ups without any loss of accuracy using the proposed method. If the number of best speaker is reduced, the Identification accuracy decreases. So, there is a trade-off between accuracy and speed-up.
Starting Page	45
Ending Page	48
File Size	332633
Page Count	4
File Format	PDF
ISBN	9781467303811
e-ISBN	9781467303828
e-ISBN	9781467303804
DOI	10.1109/ISSPA.2012.6310594
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-02
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Accuracy Silicon Vectors Training Statistics Computational modeling Sociology
Content Type	Text
Resource Type	Article

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