Spoken language parsing using phrase-level grammars and trainable classifiers

Authors:
Chad Langley;Alon Lavie;Lori Levin;Dorcas Wallace;Donna Gates;Kay Peterson
Affiliations:
Carnegie Mellon University, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA
Venue:
S2S '02 Proceedings of the ACL-02 workshop on Speech-to-speech translation: algorithms and systems - Volume 7
Year:
2002

Citing 6
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Abstract

In this paper, we describe a novel approach to spoken language analysis for translation, which uses a combination of grammar-based phrase-level parsing and automatic classification. The job of the analyzer is to produce a shallow semantic interlingua representation for spoken task-oriented utterances. The goal of our hybrid approach is to provide accurate real-time analyses while improving robustness and portability to new domains and languages.