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Isolated Myanmar Speech Recognition via ANN

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dc.contributor.author Hsan, Nan Phyu Phyu
dc.contributor.author Oo, Twe Ta
dc.date.accessioned 2019-10-15T12:30:48Z
dc.date.available 2019-10-15T12:30:48Z
dc.date.issued 2019-03
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/2292
dc.description.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). en_US
dc.language.iso en_US en_US
dc.publisher University of Computer Studies, Yangon en_US
dc.relation.ispartofseries Vol-1, Issue-1;
dc.subject ASR en_US
dc.subject isolated speech en_US
dc.subject ANN en_US
dc.subject MFCC en_US
dc.title Isolated Myanmar Speech Recognition via ANN en_US
dc.type Article en_US


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