Abstract:
This research devoted to the development
of Speech Recognition System in Bengali language
that works with speaker independent, isolated and
subword-unit-based approaches. In our work, the
original Bangla speech words were recorded and
stored as RIFF (.wav) file. Then these words were
classified into three different groups according to
the number of syllables of the speech words and
these grouping speech signals were converted to
digital form, in order to extract features. The
features were extracted by the method of Mel
Frequency Cepstrum Coefficient (MFCC) analysis.
The recognition system includes direct Euclidean
distance measurement technique. The test database
contained 600 distinct Bangla speech words and
each word was recorded from six different
speakers. The development software is written in
Turbo C and common feature of today’s software
have been included. The development system
achieved recognition rate at about 96% for single
speaker and 84.28% for multiple speakers
