This paper presents an empirical study on using syntactic and semantic information for Concept Segmentation and Labeling (CSL), a well-known component in spoken language understand- ing. Our approach is based on reranking N-best outputs from a state-of-the-art CSL parser. We perform extensive experimentation by comparing different tree-based kernels with a variety of representations of the available linguistic information, including semantic concepts, words, POS tags, shallow and full syntax, and discourse trees. The results show that the structured representa- tion with the semantic concepts yields significant improvement over the base CSL parser, much larger compared to learning with an explicit feature vector representation. We also show that shallow syntax helps improve the results and that discourse relations can be partially beneficial.

A Study of using Syntactic and Semantic Structures for Concept Segmentation and Labeling

Moschitti, Alessandro;
2014-01-01

Abstract

This paper presents an empirical study on using syntactic and semantic information for Concept Segmentation and Labeling (CSL), a well-known component in spoken language understand- ing. Our approach is based on reranking N-best outputs from a state-of-the-art CSL parser. We perform extensive experimentation by comparing different tree-based kernels with a variety of representations of the available linguistic information, including semantic concepts, words, POS tags, shallow and full syntax, and discourse trees. The results show that the structured representa- tion with the semantic concepts yields significant improvement over the base CSL parser, much larger compared to learning with an explicit feature vector representation. We also show that shallow syntax helps improve the results and that discourse relations can be partially beneficial.
2014
COLING 2014, 25th International Conference on Computational Linguistics
Dublin, Ireland
ACL
9781941643266
Iman, Saleh; Scott, Cyphers; Jim, Glass; Shafiq, Joty; Llu`ıs, M`arquez; Moschitti, Alessandro; Preslav, Nakov
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/101822
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