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NIPS
2007

Discriminative Keyword Selection Using Support Vector Machines

14 years 18 days ago
Discriminative Keyword Selection Using Support Vector Machines
Many tasks in speech processing involve classification of long term characteristics of a speech segment such as language, speaker, dialect, or topic. A natural technique for determining these characteristics is to first convert the input speech into a sequence of tokens such as words, phones, etc. From these tokens, we can then look for distinctive sequences, keywords, that characterize the speech. In many applications, a set of distinctive keywords may not be known a priori. In this case, an automatic method of building up keywords from short context units such as phones is desirable. We propose a method for the construction of keywords based upon Support Vector Machines. We cast the problem of keyword selection as a feature selection problem for n-grams of phones. We propose an alternating filter-wrapper method that builds successively longer keywords. Application of this method to language recognition and topic recognition tasks shows that the technique produces interesting and ...
William M. Campbell, Fred S. Richardson
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2007
Where NIPS
Authors William M. Campbell, Fred S. Richardson
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