Database development and automatic speech recognition of isolated Pashto spoken digits using MFCC and K-NN

International Journal of Speech Technology

Volumn 18, Issue 2, 2015, Pages 271-275

  Ali, Zakir ^a   Abbas, Arbab Waseem ^b   Thasleema, T M ^c   Uddin, Burhan ^a   Raaz, Tanzeela ^a   Abid, Sahibzada Abdur Rehman ^b  

^a THE UNIVERSITY OF AGRICULTURE   (Pakistan)

^b UNIVERSITY OF ENGINEERING AND TECHNOLOGY   (Pakistan)

^c CENTRAL UNIVERSITY OF KERALA   (India)

Author keywords

KNN; MFCC; Pashto digits

Indexed keywords

CLASSIFICATION (OF INFORMATION); SPEECH;

AUTOMATIC SPEECH RECOGNITION; K-NEAREST NEIGHBOR CLASSIFIER; KNN; LINEAR DISCRIMINATE ANALYSIS; MEL FREQUENCY CEPSTRAL CO-EFFICIENT; MFCC; NOISE-FREE ENVIRONMENTS; PASHTO DIGITS;

SPEECH RECOGNITION;

EID: 84939972118     PISSN: 13812416     EISSN: 15728110     Source Type: Journal    
DOI: 10.1007/s10772-014-9267-z     Document Type: Article

References (17)

1. Abbas, A. W., Ahmad, N., & Ali, H. (2012). Pashto spoken digits database for the automatic speech recognition research. In 18th IEEE international conference on automation and computing (ICAC), 2012 (pp. 1–5).
2. Abdur, S., Abid, R., Ahmad, N., Khan, M. A. A., & Zuhra, F. T. (2013). Concatenative based Pashto digits and numbers synthesizer. International Journal of Computer Applications, 72(6), 38–42.
3. Ádám, N. A. (2014). Speech analysis system based on vector quantization using the LBG algorithm and self-organizing maps. International Journal of Computer and Information Technology, 3(5), 952–957.
4. Alotaibi, Y. A. (2003). High performance Arabic digits recognizer using neural networks. In 2003 IEEE proceedings of the international joint conference on neural networks (Vol. 1, pp. 670–674).
5. Alcaraz Meseguer, N. (2009). Speech analysis for automatic speech recognition. Department of Electronics and Telecommunications, Norwegian University of Science and Technology (Thesis).
6. Halpern, J. (2007). The challenges and pitfalls of Arabic romanization and arabization. In Proceedings of the workshop on computational approaches to Arabic script based language.
7. Han, J., & Kamber, M. (2006). Data mining, Southeast Asia edition: Concepts and techniques (pp. 263–264). Burlington: Morgan Kaufmann.
8. Jan, Z., Abrar, M., Bashir, S., & Mirza, A. M. (2009). Seasonal to inter-annual climate prediction using data mining KNN technique. In Wireless networks, information processing and systems (pp. 40–51). Berlin: Springer.
9. Karpagavalli, S., Rani, K. U., Deepika, R., & Kokila, P. (2012). Isolated Tamil digits speech recognition using vector quantization. Paper presented at the International Journal of Engineering Research and Technology. PSGR Krishnammal College for Women, Coimbatore, 1(4), June 2012.
10. Majeed, S. A., Husain, H., Samad, S. A., & Hussain, A. (2012). Hierarchical K-means algorithm applied on isolated Malay digit speech recognition. In International proceedings of computer science & information technology (Vol. 34).
11. Muhammad, G., Alotaibi, Y. A., & Huda, M. N. (2009). Automatic speech recognition for Bangla digits. In 12th IEEE international conference on computers and information technology, 2009, (ICCIT’09) (pp. 379–383).
12. Muda, L., Begam, M., & Elamvazuthi, I. (2010). Voice recognition algorithms using mel frequency cepstral coefficient (MFCC) and dynamic time warping (DTW) techniques. arXiv preprint arXiv:1003.4083.
13. Pei, J. I. A. (2010). Automatic speech recognition. London: Springer.
14. Poonkuzhali, C., Karthiprakash, R., Valarmathy, S., & Kalamani, M. (2013). An approach to feature selection algorithm based on ant colony optimization for automatic speech recognition. pp. 5671–5678.
15. Prasad, R., Tsakalidis, S., Bulyko, I., Kao, C. L., & Natarajan, P. (2010). Pashto speech recognition with limited pronunciation lexicon. In 2010 IEEE international conference on acoustics speech and signal processing (ICASSP) (pp. 5086–5089).
16. Shah, F. (2010). Isolated Malayalam digit recogntion using Support Vector Machines. In 2010 international conference on communication control and computing technologies (pp. 692–695).
17. Sheena, C. V., Thasleema, T. M., & Narayanan, N. K. (2013). Search time reduction using hidden markov models for isolated digit recognition (pp. 33–38). Department of Information Technology, Kannur University, Kerala.