NDLI: Efficient discriminative training of long-span language models

Content Provider	IEEE Xplore Digital Library
Author	Rastrow, A. Dredze, M. Khudanpur, S.
Copyright Year	2011
Description	Author affiliation: Human Language Technology Center of Excellence, Center for Language and Speech Processing, Johns Hopkins University, Baltimore, MD USA (Rastrow, A.; Dredze, M.; Khudanpur, S.)
Abstract	Long-span language models, such as those involving syntactic dependencies, produce more coherent text than their n-gram counterparts. However, evaluating the large number of sentence-hypotheses in a packed representation such as an ASR lattice is intractable under such long-span models both during decoding and discriminative training. The accepted compromise is to rescore only the N-best hypotheses in the lattice using the long-span LM. We present discriminative hill climbing, an efficient and effective discriminative training procedure for long-span LMs based on a hill climbing rescoring algorithm [1]. We empirically demonstrate significant computational savings as well as error-rate reduction over N-best training methods in a state of the art ASR system for Broadcast News transcription.
Starting Page	214
Ending Page	219
File Size	193209
Page Count	6
File Format	PDF
ISBN	9781467303651
e-ISBN	9781467303675
e-ISBN	9781467303668
DOI	10.1109/ASRU.2011.6163933
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-11
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Lattices Acoustics Syntactics Speech Feature extraction Complexity theory
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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