Domain Specific Speech Acts for Spoken Language Translation

We describe a coding scheme for machine translation of spoken taskoriented dialogue. The coding scheme covers two levels of speaker intention − domain independent speech acts and domain dependent domain actions. Our database contains over 14,000 tagged sentences in English, Italian, and German. We argue that domain actions, and not speech acts, are the relevant discourse unit for improving translation quality. We also show that, although domain actions are domain specific, the approach scales up to large domains without an explosion of domain actions and can be coded with high inter-coder reliability across research sites. Furthermore, although the number of domain actions is on the order of ten times the number of speech acts, sparseness is not a problem for the training of classifiers for identifying the domain action. We describe our work on developing high accuracy speech act and domain action classifiers, which is the core of the source language analysis module of our NESPOLE machine translation system.

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