Abstract : In this paper we propose an enhancement of the Jacobian adaptation by estimating automatically a noise over estimation factor which yields to a closer approximation of Parallel model combination (PMC) than the traditional Jacobian adaptation. Noise over estimation factors are estimated at run-time for a set of clustered Gaussians obtained on the training set. Experiments conducted on a French natural number database show that similar performance as PMC can be obtained at the expense of a slight increase in computational complexity as compared to Jacobian adaptation.
https://hal.inria.fr/inria-00107578
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Christophe Cerisara, Jean-Claude Junqua, Luca Rigazio. Dynamic estimation of a noise over estimation factor for Jacobian-based adaptation. IEEE International Conference on Acoustics, Speech, and Signal Processing - ICASSP 2002, 2002, Orlando, Florida, IEEE, 4 p, 2002. 〈inria-00107578〉
