Optimising figure of merit for phonetic spoken term detection

Wallace, Roy G., Vogt, Robert J., Baker, Brendan J., & Sridharan, Sridha (2010) Optimising figure of merit for phonetic spoken term detection. In Douglas, Scott (Ed.) Proceedings of the 2010 IEEE International Conference on Acoustics, Speech, and Signal Processing, The Institute of Electrical and Electronics Engineers, Inc, Dallas, Texas, pp. 5298-5301.

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This paper introduces a novel technique to directly optimise the Figure of Merit (FOM) for phonetic spoken term detection. The FOM is a popular measure of sTD accuracy, making it an ideal candiate for use as an objective function. A simple linear model is introduced to transform the phone log-posterior probabilities output by a phe classifier to produce enhanced log-posterior features that are more suitable for the STD task. Direct optimisation of the FOM is then performed by training the parameters of this model using a non-linear gradient descent algorithm. Substantial FOM improvements of 11% relative are achieved on held-out evaluation data, demonstrating the generalisability of the approach.

Impact and interest:

11 citations in Scopus
9 citations in Web of Science®
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305 since deposited on 30 Aug 2010
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ID Code: 34246
Item Type: Conference Paper
Refereed: Yes
Keywords: Spoken Term Detection, Speech Processing, Speech Recognition, Information Retrieval
DOI: 10.1109/ICASSP.2010.5494969
ISBN: 9781424442966
ISSN: 1520-6149
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Engineering Systems
Copyright Owner: Copyright 2010 IEEE
Deposited On: 30 Aug 2010 01:50
Last Modified: 29 Feb 2012 14:16

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