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ANLP
1994

Improving Language Models by Clustering Training Sentences

13 years 5 months ago
Improving Language Models by Clustering Training Sentences
Many of the kinds of language model used in speech understanding suffer from imperfect modeling of intra-sentential contextual influences. I argue that this problem can be addressed by clustering the sentences in a training corpus automatically into subcorpora on the criterion of entropy reduction, and calculating separate language model parameters for each cluster. This kind of clustering offers a way to represent important contextual effects and can therefore significantly improve the performance of a model. It also offers a reasonably automatic means to gather evidence on whether a more complex, context-sensitive model using the same general kind of linguistic information is likely to reward the effort that would be required to develop it: if clustering improves the performance of a model, this proves the existence of further context dependencies, not exploited by the unclustered model. As evidence for these claims, I present results showing that clustering improves some models but...
David M. Carter
Added 02 Nov 2010
Updated 02 Nov 2010
Type Conference
Year 1994
Where ANLP
Authors David M. Carter
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