Keyword Detection using Auto Associative Neural Network with Reference to Assamese Language

Abstract

Speech and speaker recognition has yet not achieved the state-of-the-art position. Keyword detection in audio clips is gaining importance as it contributes to the audio recognition and detection systems. In this area, very few works have been carried out. In this paper, we present our experiment on keyword detection within recorded news clips. It is based on Assamese language spoken by Assamese native speakers. For this experiment, the audio clips are collected from local TV news debates, whereas the keywords are recorded by random speakers. The keywords are selected for recording considering the fact that they appear somewhere within the audio clips for a finite number of times. Mel Frequency Cepstral Coefficient (MFCC) is considered as feature and Auto Associative Neural Network (AANN) is considered as the classifier tool. With this detection model an average accuracy of 87% is achieved.