Subspace Gaussian mixture model: Difference between revisions

Revision as of 07:49, 25 September 2014

Latest revision as of 22:51, 24 June 2025

(7 intermediate revisions by 5 users not shown)

Line 1:

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

{{refmore improvecitations needed|date=September 2014}}

'''Subspace Gaussian Mixturemixture Modelmodel''' ('''SGMM''') is an acoustic modeling approach in which all phonetic states share a common Gaussian Mixture[[mixture Modelmodel]] 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 - 43334330–33, doi:10.1109/ICASSP.2010.5495662</ref>

== References ==

{{reflist}}

{{computer science stub}}

[[Category:Speech recognition]]

{{Speech-recognition-stub}}