DocumentCode :
1749710
Title :
Portability of syntactic structure for language modeling
Author :
Chelba, Ciprian
Author_Institution :
Microsoft Speech.Net/Res., Redmond, WA, USA
Volume :
1
fYear :
2001
fDate :
2001
Abstract :
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 (NLP-win) for the ATIS data and to using a small amount of data manually parsed at UPenn for gathering the initial 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%
Keywords :
grammars; natural languages; parameter estimation; probability; ATIS; Air Travel Information System; Microsoft rule-based parser; NLP-win; UPenn; Wall Street Journal; language modeling; perplexity; portability; statistical syntactic knowledge; syntactic structure; Error analysis; Information systems; Performance evaluation; Statistics; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on
Conference_Location :
Salt Lake City, UT
ISSN :
1520-6149
Print_ISBN :
0-7803-7041-4
Type :
conf
DOI :
10.1109/ICASSP.2001.940888
Filename :
940888
Link To Document :
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