Generating a task-adapted acoustic model from one or more different corpora
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United States of America Patent
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Aug 28, 2007
Grant Date -
Feb 16, 2006
app pub date -
Sep 29, 2005
filing date -
Mar 20, 2002
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Abstract
The present invention generates a task-dependent acoustic model from a supervised task-independent corpus and further adapted it with an unsupervised task dependent corpus. The task-independent corpus includes task-independent training data which has an acoustic representation of words and a sequence of transcribed words corresponding to the acoustic representation. A relevance measure is defined for each of the words in the task-independent data. The relevance measure is used to weight the data associated with each of the words in the task-independent training data. The task-dependent acoustic model is then trained based on the weighted data for the words in the task-independent training data.
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