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CSL
2011
Springer

The subspace Gaussian mixture model - A structured model for speech recognition

8 years 1 months ago
The subspace Gaussian mixture model - A structured model for speech recognition
We describe a new approach to speech recognition, in which all Hidden Markov Model (HMM) states share the same Gaussian Mixture Model (GMM) structure with the same number of Gaussians in each state. The model is defined by vectors associated with each state with a dimension of, say, 50, together with a global mapping from this vector space to the space of parameters of the GMM. This model appears to give better results than a conventional model, and the extra structure offers many new opportunities for modeling innovations while maintaining compatibility with most standard techniques.
Daniel Povey, Lukas Burget, Mohit Agarwal, Pinar A
Added 13 May 2011
Updated 13 May 2011
Type Journal
Year 2011
Where CSL
Authors Daniel Povey, Lukas Burget, Mohit Agarwal, Pinar Akyazi, Kai Feng, Arnab Ghoshal, Ondrej Glembek, Nagendra K. Goel, Martin Karafiát, Ariya Rastrow, Richard C. Rose, Petr Schwarz, Samuel Thomas
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