Search Key Identification in a Spoken Query using Isolated Keyword Recognition

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.