Machine Learning Paradigms for Speech Recognition: An Overview

@article{Deng2013MachineLP,
  title={Machine Learning Paradigms for Speech Recognition: An Overview},
  author={Li Deng and Xiao Li},
  journal={IEEE Transactions on Audio, Speech, and Language Processing},
  year={2013},
  volume={21},
  pages={1060-1089}
}
Automatic Speech Recognition (ASR) has historically been a driving force behind many machine learning (ML) techniques, including the ubiquitously used hidden Markov model, discriminative learning, structured sequence learning, Bayesian learning, and adaptive learning. Moreover, ML can and occasionally does use ASR as a large-scale, realistic application to rigorously test the effectiveness of a given technique, and to inspire new problems arising from the inherently sequential and dynamic… CONTINUE READING
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