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Title: | FPGA implementation for GMM-based speaker identification |
Authors: | EhKan, Phaklen Allen, Timothy Quigley, Steven F. plen07@yahoo.co.uk |
Keywords: | Field Programmable Gate Array (FPGA) Gaussian Mixture Model (GMM) Personal identification systems Biometric-based speaker identification |
Issue Date: | 2011 |
Publisher: | Hindawi Publishing Corporation |
Citation: | International Journal of Reconfigurable Computing, vol. 2011, 2011, pages 1-8 |
Abstract: | In today's society, highly accurate personal identification systems are required. Passwords or pin numbers can be forgotten or forged and are no longer considered to offer a high level of security. The use of biological features, biometrics, is becoming widely accepted as the next level for security systems. Biometric-based speaker identification is a method of identifying persons from their voice. Speaker-specific characteristics exist in speech signals due to different speakers having different resonances of the vocal tract. These differences can be exploited by extracting feature vectors such as Mel-Frequency Cepstral Coefficients (MFCCs) from the speech signal. A well-known statistical modelling process, the Gaussian Mixture Model (GMM), then models the distribution of each speaker's MFCCs in a multidimensional acoustic space. The GMM-based speaker identification system has features that make it promising for hardware acceleration. This paper describes the hardware implementation for classification of a text-independent GMM-based speaker identification system. The aim was to produce a system that can perform simultaneous identification of large numbers of voice streams in real time. This has important potential applications in security and in automated call centre applications. A speedup factor of ninety was achieved compared to a software implementation on a standard PC. |
Description: | Link to publisher's homepage at http://www.hindawi.com/ |
URI: | http://www.hindawi.com/journals/ijrc/2011/420369/ http://dspace.unimap.edu.my/123456789/11509 |
ISSN: | 1687-7195 |
Appears in Collections: | School of Computer and Communication Engineering (Articles) |
Files in This Item:
File | Description | Size | Format | |
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hindawi pdf.pdf | 717.21 kB | Adobe PDF | View/Open |
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