Subspace Gaussian mixture model: Difference between revisions

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{{Short description|Acoustic modeling approach in which all phonetic states share a common Gaussian}}

{{more citations needed|date=September 2014}}

'''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. 4330–33, doi:10.1109/ICASSP.2010.5495662</ref>

== References ==

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{{computer science Speech-recognition-stub}}