Spoken language parsing using phrase-level grammars and trainable classifiers

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.