Unconstrained Word Graph Based Keyword Spotting

DOI

10.2991/iccsee.2013.251How to use a DOI?

Keywords

spoken term detection, unconstraint word graph expansion, N-gram lattice limitation

Abstract

The performance of keyword spotting system suffers severe degradation when the index stage is so fast that the lattice may lose lots of information to retrieve the spoken terms . In this paper , We focus on this problem and present an approach named unconstraint word graph expansion (UWGE) to keep the pruned hypotheses which are discarded in the decoding procedure but may contain correct hypotheses. The proposed approach is to eliminate the N-gram language model state limitation of lattice and reconstruct lattice to unconstrained word graph. On two Mandarin conversation telephone speech sets, we compare performance using UWGE with that on traditional trigram lattice , and our approach gives satisfying performance gains over trigram lattice. We also show the relationship between the performance and the system speed based on this approach.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zhen Zhang
AU  - Yujing Si
AU  - Yong Liu
AU  - Qingwei Zhao
AU  - Yonghong Yan
PY  - 2013/03
DA  - 2013/03
TI  - Unconstrained Word Graph Based Keyword Spotting
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 999
EP  - 1002
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.251
DO  - 10.2991/iccsee.2013.251
ID  - Zhang2013/03
ER  -