DocumentCode :
573561
Title :
A fast search technique for discriminative keyword spotting
Author :
Tabibian, Shima ; Akbari, Ahmad ; Nasersharif, Babak
Author_Institution :
Comput. Eng. Dept., Iran Univ. of Sci. & Technol., Tehran, Iran
fYear :
2012
fDate :
2-3 May 2012
Firstpage :
140
Lastpage :
144
Abstract :
Keyword spotting systems can be divided into two main groups: HMM-based and discriminative-based systems. Some of these systems apply a phonetic search algorithm to the sequence of recognized phones to find position of target keyword in a set of speech utterances. Thus, they need a fast and accurate phonetic search algorithm to find the position of the target keyword. In this paper, we propose a hierarchical search algorithm. In each level of hierarchy, some segments of input speech will be ignored due to their low probability of being target keyword. This tends to a smaller search space and so faster search and lower computational complexity in comparison with the Viterbi algorithm which is usually used in keyword spotting applications as a phonetic search algorithm. We apply the proposed search method to the classification part of the discriminative keyword spotter introduced in our previous works. The experimental results indicate that the hierarchical search algorithm is 100 times faster than the modified Viterbi algorithm when it is used in the discriminative keyword spotting system. On the other hand, FOM of the discriminative keyword spotting system using the proposed hierarchical search algorithms degraded about 2 % in comparison to the case that this system uses a modified version of Viterbi algorithm.
Keywords :
hidden Markov models; search problems; speech processing; HMM; Viterbi algorithm; computational complexity; discriminative based systems; discriminative keyword spotting; fast search technique; hierarchical search algorithm; keyword spotting systems; phonetic search algorithm; search method; speech utterances; Classification algorithms; Complexity theory; Feature extraction; Hidden Markov models; Humans; Speech; Viterbi algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Intelligence and Signal Processing (AISP), 2012 16th CSI International Symposium on
Conference_Location :
Shiraz, Fars
Print_ISBN :
978-1-4673-1478-7
Type :
conf
DOI :
10.1109/AISP.2012.6313733
Filename :
6313733
Link To Document :
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