Active and unsupervised learning for automatic speech recognition

@inproceedings{Riccardi2003ActiveAU,
  title={Active and unsupervised learning for automatic speech recognition},
  author={Giuseppe Riccardi and Dilek Z. Hakkani-T{\"u}r},
  booktitle={INTERSPEECH},
  year={2003}
}
State-of-the-art speech recognition systems are trained using human transcriptions of speech utterances. In this paper, we describe a method to combine active and unsupervised learning for automatic speech recognition (ASR). The goal is to minimize the human supervision for training acoustic and language models and to maximize the performance given the transcribed and untranscribed data. Active learning aims at reducing the number of training examples to be labeled by automatically processing… CONTINUE READING
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