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Subspace Gaussian mixture model

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This is an old revision of this page, as edited by Eyesnore (talk | contribs) at 12:59, 24 September 2014 (Eyesnore moved page Sgmm to SGMM: Capitalization). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.

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.[1]

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  1. ^ SUBSPACE GAUSSIAN MIXTURE MODELS FOR SPEECH RECOGNITION
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