Open AccessIsolated Keyword Spotting in Multilingual Environment using ANN and MFCC
Author(s) -
Brajen Kumar Deka,
Priyanka Das
Publication year - 2020
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.c6135.049420
Subject(s) - mel frequency cepstrum , assamese , keyword spotting , computer science , artificial neural network , backpropagation , artificial intelligence , hindi , speech recognition , classifier (uml) , spotting , pattern recognition (psychology) , feature extraction , philosophy , linguistics
The performance and analysis of Keyword Spotting system (KWS) are applied when the training and testing in a multilingual environment. This paper exhibits an approach for building up a multilingual KWS framework for Assamese, English and Hindi language dependent on feed-forward neural system. Mel Frequency Cepstral Coefficient (MFCC) has been utilized for highlight extraction which gives a lot of highlight vectors from recorded sound examples. Neural Network backpropagation model is utilized to improve the acknowledgment execution on the recently made multilingual database utilizing the multi-layer feed-forward neural system classifier.