Recognition of spoken bengali numerals using MLP, SVM, RF based models with PCA based feature summarization
Joint Authors
Source
The International Arab Journal of Information Technology
Issue
Vol. 15, Issue 2 (31 Mar. 2018), pp.263-269, 7 p.
Publisher
Publication Date
2018-03-31
Country of Publication
Jordan
No. of Pages
7
Main Subjects
Information Technology and Computer Science
Abstract EN
This paper presents a method of automatic recognition of Bengali numerals spoken in noise-free and noisy environments by multiple speakers with different dialects.
Mel Frequency Cepstral Coefficients (MFCC) are used for feature extraction, and Principal Component Analysis is used as a feature summarizer to form the feature vector from the MFCC data for each digit utterance.
Finally, we use Support Vector Machines, Multi-Layer Perceptrons, and Random Forests to recognize the Bengali digits and compare their performance.
In our approach, we treat each digit utterance as a single indivisible entity, and we attempt to recognize it using features of the digit utterance as a whole.
This approach can therefore be easily applied to spoken digit recognition tasks for other languages as well.
American Psychological Association (APA)
Gupta, Avisek& Sarkar, Kamal. 2018. Recognition of spoken bengali numerals using MLP, SVM, RF based models with PCA based feature summarization. The International Arab Journal of Information Technology،Vol. 15, no. 2, pp.263-269.
https://search.emarefa.net/detail/BIM-838604
Modern Language Association (MLA)
Gupta, Avisek& Sarkar, Kamal. Recognition of spoken bengali numerals using MLP, SVM, RF based models with PCA based feature summarization. The International Arab Journal of Information Technology Vol. 15, no. 2 (Mar. 2018), pp.263-269.
https://search.emarefa.net/detail/BIM-838604
American Medical Association (AMA)
Gupta, Avisek& Sarkar, Kamal. Recognition of spoken bengali numerals using MLP, SVM, RF based models with PCA based feature summarization. The International Arab Journal of Information Technology. 2018. Vol. 15, no. 2, pp.263-269.
https://search.emarefa.net/detail/BIM-838604
Data Type
Journal Articles
Language
English
Notes
Includes appendix : p. 269
Record ID
BIM-838604