DocumentCode
2991576
Title
A subsequence-histogram method for generic vocabulary recognition over deletion channels
Author
Fozunbal, Majid
Author_Institution
Hewlett-Packard Labs., Palo Alto, CA, USA
fYear
2009
fDate
June 28 2009-July 3 2009
Firstpage
2557
Lastpage
2561
Abstract
We consider the problem of recognizing a vocabulary-a collection of words (sequences) over a finite alphabet-from a potential subsequence of one of its words. We assume the given subsequence is received through a deletion channel as a result of transmission of a random word from one of the two generic underlying vocabularies. An exact maximum a posterior (MAP) solution for this problem counts the number of ways a given subsequence can be derived from particular subsets of candidate vocabularies, requiring exponential time or space.
Keywords
maximum likelihood estimation; speech recognition; deletion channels; maximum a posterior solution; subsequence-histogram method; vocabulary recognition; Approximation algorithms; Data mining; Databases; Histograms; Laboratories; Maximum likelihood decoding; Maximum likelihood detection; Natural languages; Polynomials; Vocabulary; Classification; histogram; recognition; search; storage; subsequence;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory, 2009. ISIT 2009. IEEE International Symposium on
Conference_Location
Seoul
Print_ISBN
978-1-4244-4312-3
Electronic_ISBN
978-1-4244-4313-0
Type
conf
DOI
10.1109/ISIT.2009.5206011
Filename
5206011
Link To Document