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- W137700910 abstract "In this paper we investigate a maximum entropy approach to spoken language understanding. We compare this approach with a parser based on finite-state transducers. The parsers are evaluated on a corpus of utterances modelling human-computer interactions within a single domain. The corpus was annotated with task-oriented semantic categories to obtain a set of shallow functional parse trees. We focus our investigation on the quality of the structured concepts produced by each approach. A direct comparison shows that the maximum entropy parser achieves better performance than the finite-state parser, even with very limited training data." @default.
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- W137700910 date "2004-10-04" @default.
- W137700910 modified "2023-09-26" @default.
- W137700910 title "A maximum entropy shallow functional parser for spoken language understanding" @default.
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- W137700910 doi "https://doi.org/10.21437/interspeech.2004-231" @default.
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