NDLI: Variational sequence labeling

Content Provider	IEEE Xplore Digital Library
Author	Flamary, R. Canu, S. Rakotomamonjy, A. Rose, J.L.
Copyright Year	2009
Description	Author affiliation: CREATIS-LRMN, Université de Lyon, 69621 Villeurbanne France (Rose, J.L.) \|\| LITIS EA 4108, Université de Rouen, 76800 Saint Etienne du Rouvray France (Flamary, R.; Canu, S.; Rakotomamonjy, A.)
Abstract	Sequence labeling is concerned with processing an input data sequence and producing an output sequence of discrete labels which characterize it. Common applications includes speech recognition, language processing (tagging, chunking) and bioinformatics. Many solutions have been proposed to partially cope with this problem. These include probabilistic models (HMMs, CRFs) and machine learning algorithm (SVM, Neural nets). In practice, the best results have been obtained by combining several of these methods. However, fusing different signal segmentation methods is not straightforward, particularly when integrating prior information. In this paper the sequence labeling problem is viewed as a multi objective optimization task. Each objective targets a different aspect of sequence labelling such as good classification, temporal stability and change detection. The resulting optimization problem turns out to be non convex and plagued with numerous local minima. A region growing algorithm is proposed as a method for finding a solution to this multi functional optimization task. The proposed algorithm is evaluated on both synthetic and real data (BCI dataset). Results are encouraging and better than those previously reported on these datasets.
Starting Page	1
Ending Page	6
File Size	2682684
Page Count	6
File Format	PDF
ISBN	9781424449477
ISSN	15512541
DOI	10.1109/MLSP.2009.5306238
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-01
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Labeling Change detection algorithms Speech recognition Natural languages Tagging Bioinformatics Hidden Markov models Machine learning algorithms Support vector machines Neural networks
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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