Robust Parsing of Spoken Dialogue Using Contextual

نویسنده

  • Gerhard Hanrieder
چکیده

and Recognition Probabilities G unther G orz, Gerhard Hanrieder Bavarian Research Center for Knowledge Based Systems (FORWISS) Am Weichselgarten 7, 91058 Erlangen, Germany ABSTRACT In this paper we describe the linguistic processing component of a spoken dialogue system. The task of this word graph parser is to nd the most plausible sequence of word hypotheses in the input graph. If no global solution can be found, a robust mechanism of selecting multiple partial results is applied. We argue that the semantic accuracy of the selected results can be considerably improved if the selection is based on an integrated quality score combining word recognition probabilities and context-dependent semantic top-down predictions. Results of parsing word graphs with and without predictions are reported.

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تاریخ انتشار 1995