Classification of vowel sounds using MFCC and feed forward neural network
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Institute of Electrical and Elctronics Engineering (IEEE)
2010
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my.unimap-86542010-08-13T06:06:39Z Classification of vowel sounds using MFCC and feed forward neural network Paulraj, Murugesa Pandiyan, Prof. Madya Sazali, Yaacob, Prof. Dr. Nazri, A. Kumar, S. Digital signal processing Mel-frequency cepstrsal coefficients Phonemes Speech to text translation International Colloquium on Signal Processing and Its Applications (CSPA) Link to publisher's homepage at http://ieeexplore.ieee.org/ The English language as spoken by Malaysians varies from place to place and differs from one ethnic community and its sub-group to another. Hence, it is necessary to develop an exclusive Speech to text translation system for understanding the English pronunciation as spoken by Malaysians. Speech translation is a process of both speech recognition and equivalent phonemic to word translation. Speech recognition is a process of identifying phonemes from the speech segment. In this paper, the initial step for speech recognition by identifying the phoneme features is proposed. In order to classify the phoneme features, Mel-frequency cepstral coefficients (MFCC) are computed in this paper. A simple feed forward Neural Network (FFNN) trained by back propagation procedure is proposed for identifying the phonemes features. The extracted MFCC coefficients are used as input to a neural network classifier for associating it to one of the 11 classes. 2010-08-13T06:06:39Z 2010-08-13T06:06:39Z 2009-03-06 Working Paper p.59-62 978-1-4244-4150-1 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5069189 http://hdl.handle.net/123456789/8654 en Proceedings of the 5th International Colloquium on Signal Processing and Its Applications (CSPA) 2009 Institute of Electrical and Elctronics Engineering (IEEE) |
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Universiti Malaysia Perlis |
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Asia |
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Malaysia |
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Universiti Malaysia Perlis |
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http://dspace.unimap.edu.my/ |
| language |
English |
| topic |
Digital signal processing Mel-frequency cepstrsal coefficients Phonemes Speech to text translation International Colloquium on Signal Processing and Its Applications (CSPA) |
| spellingShingle |
Digital signal processing Mel-frequency cepstrsal coefficients Phonemes Speech to text translation International Colloquium on Signal Processing and Its Applications (CSPA) Paulraj, Murugesa Pandiyan, Prof. Madya Sazali, Yaacob, Prof. Dr. Nazri, A. Kumar, S. Classification of vowel sounds using MFCC and feed forward neural network |
| description |
Link to publisher's homepage at http://ieeexplore.ieee.org/ |
| format |
Working Paper |
| author |
Paulraj, Murugesa Pandiyan, Prof. Madya Sazali, Yaacob, Prof. Dr. Nazri, A. Kumar, S. |
| author_facet |
Paulraj, Murugesa Pandiyan, Prof. Madya Sazali, Yaacob, Prof. Dr. Nazri, A. Kumar, S. |
| author_sort |
Paulraj, Murugesa Pandiyan, Prof. Madya |
| title |
Classification of vowel sounds using MFCC and feed forward neural network |
| title_short |
Classification of vowel sounds using MFCC and feed forward neural network |
| title_full |
Classification of vowel sounds using MFCC and feed forward neural network |
| title_fullStr |
Classification of vowel sounds using MFCC and feed forward neural network |
| title_full_unstemmed |
Classification of vowel sounds using MFCC and feed forward neural network |
| title_sort |
classification of vowel sounds using mfcc and feed forward neural network |
| publisher |
Institute of Electrical and Elctronics Engineering (IEEE) |
| publishDate |
2010 |
| url |
http://dspace.unimap.edu.my/xmlui/handle/123456789/8654 |
| _version_ |
1643789248732594176 |
| score |
13.214268 |