MODEL ADAPTATION BASED ON HMM DECOMPOSITION FOR REVERBERANT SPEECH RECOGNITION

@inproceedings{RAQiang2004MODELAB,
  title={MODEL ADAPTATION BASED ON HMM DECOMPOSITION FOR REVERBERANT SPEECH RECOGNITION},
  author={AMU RA'Qiang},
  year={2004}
}
  • AMU RA'Qiang
  • Published 2004
The performance of a speech recognizer is degraded drastically in reverberant environments. We proposed a novel algorithm which can model an observation signal by composition of HMMs of clean speech, noise and an acoustic transfer function(l]. However, how to estimate HMM parameters of the acoustic transfer function is a remaining serious problem. In our previous paperll], we measured real impulse responses of training positions in an experiment room. It is inconvenient and unrealistic to… CONTINUE READING

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