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Phone deactivation pruning in large vocabulary continuous speech recognition

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Renals 1996 Signal Processing Letters.pdf (326.3Kb)
Date
01/1996
Author
Renals, Steve
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Abstract
In this letter, we introduce a new pruning strategy for large vocabulary continuous speech recognition based on direct estimates of local posterior phone probabilities. This approach is well suited to hybrid connectionist/hidden Markov model systems. Experiments on the Wall Street Journal task using a 20000 word vocabulary and a trigram language model have demonstrated that phone deactivation pruning can increase the speed of recognition-time search by up to a factor of 10, with a relative increase in error rate of less than 2%.
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http://ieeexplore.ieee.org/xpl/tocresult.jsp?isYear=1996&isnumber=10187&Submit32=Go+To+Issue

http://hdl.handle.net/1842/1084
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