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Framewise phone classification using support vector machines

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Salomon_King_Osborne_icslp2002.pdf (73.86Kb)
Date
09/2002
Author
Salomon, Jesper
King, Simon
Osborne, Miles
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Abstract
We describe the use of Support Vector Machines for phonetic classification on the TIMIT corpus. Unlike previous work, in which entire phonemes are classified, our system operates in a framewise manner and is intended for use as the front-end of a hybrid system similar to ABBOT. We therefore avoid the problems of classifying variable-length vectors. Our frame-level phone classification accuracy on the complete TIMIT test set is competitive with other results from the literature. In addition, we address the serious problem of scaling Support Vector Machines by using the Kernel Fisher Discriminant.
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http://www.isca-speech.org/archive/icslp02

http://hdl.handle.net/1842/956
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  • Linguistics and English Language publications

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