Subspace Gaussian mixture model: Difference between revisions

Revision as of 06:44, 25 September 2014

Revision as of 06:45, 25 September 2014

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'''Subspace Gaussian Mixture Model''' ('''SGMM)''') is an acoustic modeling approach in which all phonetic states share a common Gaussian Mixture Model structure, and the means and mixture weights vary in a subspace of the total parameter space.<ref>Povey, D : Burget, L. ; Agarwal, M. ; Akyazi, P. "Subspace Gaussian Mixture Models for speech recognition", IEEE, 2010, Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on, pp. 4330 - 4333, doi:10.1109/ICASSP.2010.5495662</ref>

== References ==