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ICASSP
2011
IEEE
12 years 7 months ago
Soft frame margin estimation of Gaussian Mixture Models for speaker recognition with sparse training data
—Discriminative Training (DT) methods for acoustic modeling, such as MMI, MCE, and SVM, have been proved effective in speaker recognition. In this paper we propose a DT method fo...
Yan Yin, Qi Li
ICPR
2010
IEEE
13 years 10 months ago
Dimension-Decoupled Gaussian Mixture Model for Short Utterance Speaker Recognition
The Gaussian Mixture Model (GMM) is often used in conjunction with Mel-frequency cepstral coefficient (MFCC) feature vectors for speaker recognition. A great challenge is to use ...
Thilo Stadelmann, Bernd Freisleben
INTERSPEECH
2010
12 years 10 months ago
Bayesian speaker recognition using Gaussian mixture model and laplace approximation
This paper presents a Bayesian approach for Gaussian mixture model (GMM)-based speaker identification. Some approaches evaluate the speaker score of a test speech utterance using ...
Shih-Sian Cheng, I-Fan Chen, Hsin-Min Wang
JDCTA
2010
144views more  JDCTA 2010»
12 years 10 months ago
Research on SVDD Applied in Speaker Verification
In tradition probability statistics model, speaker verification threshold is instability in different test situations. A novel speaker verification method based on Support Vector ...
Yuhuan Zhou, Xiongwei Zhang, Jinming Wang, Yong Go...
ICASSP
2011
IEEE
12 years 7 months ago
Estimation of fundamental frequency from surface electromyographic data: EMG-to-F0
In this paper, we present our recent studies of F0 estimation from the surface electromyographic (EMG) data using a Gaussian mixture model (GMM)-based voice conversion (VC) techni...
Keigo Nakamura, Matthias Janke, Michael Wand, Tanj...