Multi-View Semi-Supervised Learning for Dialog Act Segmentation of Speech

@article{Gz2010MultiViewSL,
  title={Multi-View Semi-Supervised Learning for Dialog Act Segmentation of Speech},
  author={{\"U}mit G{\"u}z and S{\'e}bastien Cuendet and Dilek Z. Hakkani-T{\"u}r and G{\"o}khan T{\"u}r},
  journal={IEEE Transactions on Audio, Speech, and Language Processing},
  year={2010},
  volume={18},
  pages={320-329}
}
Sentence segmentation of speech aims at determining sentence boundaries in a stream of words as output by the speech recognizer. Typically, statistical methods are used for sentence segmentation. However, they require significant amounts of labeled data, preparation of which is time-consuming, labor-intensive, and expensive. This work investigates the application of multi-view semi-supervised learning algorithms on the sentence boundary classification problem by using lexical and prosodic… CONTINUE READING
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