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Exemplar-based joint channel and noise compensation
2013
2013 IEEE International Conference on Acoustics, Speech and Signal Processing
In this paper two models for channel estimation in exemplar-based noise robust speech recognition are proposed. Building on a compositional model that models noisy speech and a combination of noise and speech atoms, the first model iteratively estimates a filter to best compensate the mismatch with the observed noisy speech. The second model estimates separate filters for the noise and speech atoms. We show that both models enable noise-robust ASR even if the channel characteristics of the
doi:10.1109/icassp.2013.6637772
dblp:conf/icassp/GemmekeVD13
fatcat:v4cndeq44jh4bemrysr3pa56qm