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Reseach Article

Search Key Identification in a Spoken Query using Isolated Keyword Recognition

by Utpal Bhattacharjee
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 5 - Number 8
Year of Publication: 2010
Authors: Utpal Bhattacharjee
10.5120/933-1310

Utpal Bhattacharjee . Search Key Identification in a Spoken Query using Isolated Keyword Recognition. International Journal of Computer Applications. 5, 8 ( August 2010), 14-21. DOI=10.5120/933-1310

@article{ 10.5120/933-1310,
author = { Utpal Bhattacharjee },
title = { Search Key Identification in a Spoken Query using Isolated Keyword Recognition },
journal = { International Journal of Computer Applications },
issue_date = { August 2010 },
volume = { 5 },
number = { 8 },
month = { August },
year = { 2010 },
issn = { 0975-8887 },
pages = { 14-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume5/number8/933-1310/ },
doi = { 10.5120/933-1310 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:53:42.643606+05:30
%A Utpal Bhattacharjee
%T Search Key Identification in a Spoken Query using Isolated Keyword Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 5
%N 8
%P 14-21
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This article presents a novel technique for the recognition of isolated keywords from spoken search queries. Recognition of the isolated keywords from spoken search queries may be considered as the first step towards the development of a speech-operated keyword-based searching technique. A database of 300 spoken search queries from Assamese language, a major Indian language mostly spoken by the people of north east India, has been created. The system developed during the study has been tested and evaluated with the above mentioned database. In the present study, Mel Frequency Cepstral Coefficient (MFCC) has been used as the feature vector and Multilayer Perceptron (MLP) to identify the phoneme boundaries as well as for recognition of the phonemes. Viterbi search technique has been used to identify the keywords from the sequence of phonemes generated by the phoneme recognizer. A recognition accuracy of 74.67% has been achieved in the present study.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Query Identification Phoneme Segmentation Multilayer Perceptron Viterbi Search