Mixture autoregressive hidden Markov models for speech signals

@article{Juang1985MixtureAH,
  title={Mixture autoregressive hidden Markov models for speech signals},
  author={B. Juang and L. Rabiner},
  journal={IEEE Trans. Acoust. Speech Signal Process.},
  year={1985},
  volume={33},
  pages={1404-1413}
}
  • B. Juang, L. Rabiner
  • Published 1985
  • Mathematics, Computer Science
  • IEEE Trans. Acoust. Speech Signal Process.
In this paper a signal modeling technique based upon finite mixture autoregressive probabilistic functions of Markov chains is developed and applied to the problem of speech recognition, particularly speaker-independent recognition of isolated digits. Two types of mixture probability densities are investigated: finite mixtures of Gaussian autoregressive densities (GAM) and nearest-neighbor partitioned finite mixtures of Gaussian autoregressive densities (PGAM). In the former (GAM), the… Expand
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