Large Margin Training of Continuous Density Hidden Markov Models

@inproceedings{Sha2007LargeMT,
  title={Large Margin Training of Continuous Density Hidden Markov Models},
  author={Fei Sha},
  year={2007}
}
Continuous density hidden Markov models (CD-HMMs) are an essential component of modern systems for automatic speech recognition (ASR). These models assign probabilities to the sequences of acoustic feature vectors extracted by signal processing of speech waveforms. In this chapter, we investigate a new framework for parameter estimation in CD-HMMs. Our framework is inspired by recent parallel trends in the fields of ASR and machine learning. In ASR, significant improvements in performance have… CONTINUE READING

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