DocumentCode
1050125
Title
On the bias of the Turing-Good estimate of probabilities
Author
Juang, B.H. ; Lo, S.H.
Author_Institution
AT&T Bell Labs., Murray Hill, NJ, USA
Volume
42
Issue
2
fYear
1994
fDate
2/1/1994 12:00:00 AM
Firstpage
496
Lastpage
498
Abstract
Good´s (1953) estimate, based on Turing´s formula, was suggested for estimating the probabilities of words in text as well as of species in a mixed population and was found particularly useful for the probability of unseen classes. The authors address the issue of bias in Good´s estimate and propose an alternative to reduce this bias. This may be important in the construction of a language model for speech recognition where sparse data and low probability events are key problems
Keywords
estimation theory; probability; speech recognition; Turing-Good probability estimate; bias; language model; low probability events; mixed population; sparse data; species; speech recognition; text; words; Bayesian methods; Maximum likelihood estimation; Natural languages; Probability; Speech recognition; Text analysis; Tin; Vocabulary;
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/78.275640
Filename
275640
Link To Document