Abstract:
Automatic Speech Recognition (ASR) is a popular
and challenging area of research in human computer
interaction. This paper presents an isolated Myanmar
speech recognition system that is speaker dependent
as well as speaker independent and developed by
using Artificial Neural Network techniques. In this
system, the Mel Frequency Cepstral Coefficients
extracted from the manually preprocessed words are
considered as the features to acoustically identify the
speeches. Those features are then used to train and
test the Backpropagation neural network model. This
system uses a database of 2800 utterances (names of
the cities in Myanmar) by 10 talkers (4 males and 6
females), from which 2400 utterances are used for
training and 400 are used for testing and recognition.
As per the experimental results, the proposed system
achieved the recognition rate of about 93.5% for
known speakers (i.e., speaker dependent) and 76.5%
for unknown speakers (i.e., speaker independent).
