Gauss karışım modeli tabanlı konuşmacı belirleme sistemlerinde klasik MAP uyarlanması yönteminin performans analizi
Type :
Conference paper
Publication Status :
published
Access :
restrictedAccess
Abstract
Gaussian mixture models (GMM) is one of the most commonly used methods in text-independent speaker identification systems. In this paper, performance of the GMM approach has been measured with different parameters and settings. Voice activity detection (VAD) component has been found to have a significant impact on the performance. Therefore, VAD algorithms that are robust to background noise have been proposed. Significant differences in performance have been observed between male and female speakers and GSM/PSTN channels. Moreover, single-stream GMM approach has been found to perform significantly better than the multi-stream GMM approach. It has been observed under all conditions that data duration is critical for good performance.
Source :
Signal Processing and Communications Applications Conference (SIU), 2010 IEEE 18th
Date :
2010
Publisher :
IEEE
URI
http://hdl.handle.net/10679/2377http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=5651366
Collections
Share this page