RECAL — A language identification system

摘要

Since the inception of IT, one of the primary concerns has been to build devices with easy interactivity. Speech can be considered as one of the most preferred and easiest modes of interaction. Speech Recognition is the technique of automatically identifying spoken words from voice signals. Due to the multilingual nature of our country, we are habituated in using a mixture of languages in the course of verbal interaction and so, prior to recognizing speech, it is essential to determine the respective languages to which the spoken words belong. RECAL (Record Extract Classify According to Language) is a system, aimed towards identification of languages from multilingual voice signals. To start with, Mel Scale Cepstral Coefficient (MFCC) based features have been used to model languages using 9300 uttered numerals amidst 3 languages (English, Bangla and Hindi). An accuracy of 98.39% has been obtained considering the similarity between Bangla and Hindi numerals and avoidance of noise gating to simulate real world environment.