Unsupervised discovery and training of maximally dissimilar cluster models

@inproceedings{Beaufays2010UnsupervisedDA,
  title={Unsupervised discovery and training of maximally dissimilar cluster models},
  author={Françoise Beaufays and Vincent Vanhoucke and Brian Strope},
  booktitle={INTERSPEECH},
  year={2010}
}
One of the difficult problems of acoustic modeling for Automatic Speech Recognition (ASR) is how to adequately model the wide variety of acoustic conditions which may be present in the data. The problem is especially acute for tasks such as Google Search by Voice, where the amount of speech available per transaction is small, and adaptation techniques start showing their limitations. As training data from a very large user population is available however, it is possible to identify and jointly… CONTINUE READING
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