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SPEECH
2008
124views more  SPEECH 2008»
13 years 5 months ago
Statistical mapping between articulatory movements and acoustic spectrum using a Gaussian mixture model
In this paper, we describe a statistical approach to both an articulatory-to-acoustic mapping and an acoustic-to-articulatory inversion mapping without using phonetic information....
Tomoki Toda, Alan W. Black, Keiichi Tokuda
ICPR
2006
IEEE
14 years 6 months ago
Mixture of Support Vector Machines for HMM based Speech Recognition
Speech recognition is usually based on Hidden Markov Models (HMMs), which represent the temporal dynamics of speech very efficiently, and Gaussian mixture models, which do non-opt...
Sven E. Krüger, Martin Schafföner, Marce...
ICPR
2010
IEEE
13 years 3 months ago
Information Theoretic Expectation Maximization Based Gaussian Mixture Modeling for Speaker Verification
The expectation maximization (EM) algorithm is widely used in the Gaussian mixture model (GMM) as the state-of-art statistical modeling technique. Like the classical EM method, th...
Sheeraz Memon, Margaret Lech, Namunu Chinthaka Mad...
ICASSP
2008
IEEE
14 years 6 days ago
Maximum likelihood approach to speech enhancement for noisy reverberant signals
This paper proposes a speech enhancement method for signals contaminated by room reverberation and additive background noise. The following conditions are assumed: (1) The spectra...
Takuya Yoshioka, Tomohiro Nakatani, Takafumi Hikic...
ICASSP
2010
IEEE
13 years 6 months ago
Multilingual acoustic modeling for speech recognition based on subspace Gaussian Mixture Models
Although research has previously been done on multilingual speech recognition, it has been found to be very difficult to improve over separately trained systems. The usual approa...
Lukas Burget, Petr Schwarz, Mohit Agarwal, Pinar A...