Improved topic classification and keyword discovery using an HMM-based speech recognizer trained without supervision

@inproceedings{Siu2010ImprovedTC,
  title={Improved topic classification and keyword discovery using an HMM-based speech recognizer trained without supervision},
  author={Man-Hung Siu and Herbert Gish and Arthur Chan and William Belfield},
  booktitle={INTERSPEECH},
  year={2010}
}
In our previous publication [1], we presented a new approach to HMM training, viz., training without supervision. We used an HMM trained without supervision for transcribing audio into self-organized units (SOUs) for the purpose of topic classification. In this paper we report improvements made to the system, including the use of context dependent acoustic models and lattice based features that together reduce the topic verification equal error rate from 12% to 7%. In addition to discussing the… CONTINUE READING
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Unsupervised training of an HMM-based speech recognition system for topic classification

  • H. Gish, M. Siu, A. Chan andW. Belfield
  • Interspeech 2009.
  • 2009
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