TR-2009-02
An Experimental Evaluation of Keyword-Filler Hidden Markov Models
Aren Jansen; Partha Niyogi. 16 April, 2009.
Communicated by Partha Niyogi.
Abstract
We present the results of a small study involving the use of keyword-filler hidden
Markov models (HMM) for spotting keywords in continuous speech. The
performance dependence on the amount of keyword training data and the choice
of model parameters is documented. Also, we demonstrate a strong correlation between
individual keyword spotting performance and median duration of that keyword.
This dependence highlights the inadequacy of reporting system performance
in terms of averages over arbitrary keyword sets, which is typically done for this
task.
Original Document
The original document is available in PDF (uploaded 16 April, 2009 by
Partha Niyogi).
