|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
A PLSA-BASED LANGUAGE MODEL FOR CONVERSATIONAL TELEPHONE SPEECH
David Mrva and Philip C. Woodland
This paper describes experiments with a PLSA-based language model for conversational telephone speech. This model uses a long-range history and exploits topic information in the test text to adjust probabilities of test words. The PLSA-based model was found to lower test set perplexity over a traditional word+class-based 4-gram by 13% (optimistic estimate using a reference transcript as history) or by 6% (realistic estimate using recognised transcript as history). Moreover, this paper introduces a use of confidence scores to weight words in the history, a weight of the prior topic distribution and a way of calculating perplexity that accounts for recognition errors in the model context.
If you have difficulty viewing files that end
which are gzip compressed, then you may be able to find
tools to uncompress them at the gzip
If you have difficulty viewing files that are in PostScript, (ending
'.ps.gz'), then you may be able to
find tools to view them at
We have attempted to provide automatically generated PDF copies of documents for which only PostScript versions have previously been available. These are clearly marked in the database - due to the nature of the automatic conversion process, they are likely to be badly aliased when viewed at default resolution on screen by acroread.
|| Search | CUED | Cambridge University ||
2005 Cambridge University Engineering Dept
Information provided by milab-maintainer