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David Imseng

2 accepted papers

2015

Building context-dependent DNN acoustic models using Kullback-Leibler divergence-based state tying

Gábor Gosztolya, Tamás Grósz, László Tóth, David Imseng
ICASSP 2015accepted

Deep neural network (DNN) based speech recognizers have recently replaced Gaussian mixture (GMM) based systems as the state-of-the-art. HMM/DNN systems have kept many refinements of the HMM/GMM framework, even though some of these may be suboptimal for them. One such example is the creation of conte…

Cited by 0Source ↗Scholar ↗
2015

Learning feature mapping using deep neural network bottleneck features for distant large vocabulary speech recognition

Ivan Himawan, Petr Motlícek, David Imseng, Blaise Potard, Namhoon Kim, Jaewon Lee
ICASSP 2015accepted

Automatic speech recognition from distant microphones is a difficult task because recordings are affected by reverberation and background noise. First, the application of the deep neural network (DNN)/hidden Markov model (HMM) hybrid acoustic models for distant speech recognition task using AMI meet…

Cited by 0Source ↗Scholar ↗