Portability of Syntactic Structure for Language Modeling

dc.creatorChelba, Ciprian
dc.date2001-08-29
dc.date.accessioned2026-07-07T03:17:26Z
dc.date.available2026-07-07T03:17:26Z
dc.descriptionThe paper presents a study on the portability of statistical syntactic knowledge in the framework of the structured language model (SLM). We investigate the impact of porting SLM statistics from the Wall Street Journal (WSJ) to the Air Travel Information System (ATIS) domain. We compare this approach to applying the Microsoft rule-based parser (NLPwin) for the ATIS data and to using a small amount of data manually parsed at UPenn for gathering the intial SLM statistics. Surprisingly, despite the fact that it performs modestly in perplexity (PPL), the model initialized on WSJ parses outperforms the other initialization methods based on in-domain annotated data, achieving a significant 0.4% absolute and 7% relative reduction in word error rate (WER) over a baseline system whose word error rate is 5.8%; the improvement measured relative to the minimum WER achievable on the N-best lists we worked with is 12%.
dc.descriptionICASSP 2001, Salt Lake City; 4 pages
dc.identifierhttps://arxiv.org/abs/cs/0108022
dc.identifierhttp://arxiv.org/abs/cs/0108022
dc.identifierICASSP 2001 Proceedings
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/30725
dc.subjectComputation and Language
dc.subjectI.2.7
dc.titlePortability of Syntactic Structure for Language Modeling
dc.typetext

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