Learning When to Listen: Detecting System-Addressed Speech in Human-Human-Computer Dialog

@inproceedings{Shriberg2012LearningWT,
  title={Learning When to Listen: Detecting System-Addressed Speech in Human-Human-Computer Dialog},
  author={Elizabeth Shriberg and Andreas Stolcke and Dilek Z. Hakkani-T{\"u}r and Larry P. Heck},
  booktitle={INTERSPEECH},
  year={2012}
}
New challenges arise for addressee detection when multiple people interact jointly with a spoken dialog system using unconstrained natural language. We study the problem of discriminating computer-directed from human-directed speech in a new corpus of human-human-computer (H-H-C) dialog, using lexical and prosodic features. The prosodic features use no word, context, or speaker information. Results with 19% WER speech recognition show improvements from lexical features (EER=23.1%) to prosodic… CONTINUE READING
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