Information Services banner Edinburgh Research Archive The University of Edinburgh crest

Edinburgh Research Archive >
Centre for Speech Technology Research >
CSTR publications >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1842/1186

This item has been viewed 20 times in the last year. View Statistics

Files in This Item:

File Description SizeFormat
icassp99.pdf158.94 kBAdobe PDFView/Open
icassp99.ps.gz55.77 kBGzipped PostscriptView/Open
Title: Named entity tagged language models.
Authors: Gotoh, Yoshihiko
Renals, Steve
Williams, Gethin
Issue Date: 1999
Citation: In Proc IEEE ICASSP, pages 513-516, Phoenix AZ, 1999.
Publisher: IEEE
Abstract: We introduce Named Entity (NE) Language Modelling, a stochastic finite state machine approach to identifying both words and NE categories from a stream of spoken data. We provide an overview of our approach to NE tagged language model (LM) generation together with results of the application of such a LM to the task of out-of-vocabulary (OOV) word reduction in large vocabulary speech recognition. Using the Wall Street Journal and Broadcast News corpora, it is shown that the tagged LM was able to reduce the overall word error rate by 14%, detecting up to 70% of previously OOV words. We also describe an example of the direct tagging of spoken data with NE categories.
URI: http://hdl.handle.net/1842/1186
Appears in Collections:CSTR publications

Items in ERA are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback