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The use of meta-HMM in multistream HMM training for automatic speech recognition
1998
5th International Conference on Spoken Language Processing (ICSLP 1998)
unpublished
Among the di erent attempts to improve recognition scores and robustness to noise, the recognition of parallel streams of data each one representing partial information on the test signal and the fusion of the decisions have received a great deal of interest. The problem of training such models taking recombination constraints at the level of speech-subunits has not yet been rigorously addressed. This paper shows how equivalence with an extended meta-HMM solves the problem and how reestimation
doi:10.21437/icslp.1998-193
fatcat:orpv24522vewndjljgmp4axytm