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Abstract
Speech has many parameters such as pitch, energy, Noise, Change in speaking rate, Change in articulation. Speech is also of two type i.e. voiced speech and unvoiced speech. Voiced speech has high frequency as compared to the unvoiced speech. Many algorithms can be used to extract features of the speech. Here we use LPC ( Linear predictive coding ) method to extract the features of speech. The aim of this report is to show the difference between the feature of the child speech and adult speech. We also synthesize the speech by removing the unvoiced speech from the original speech by removing the low frequency speech from high frequency speech. This research is focused on implementing and studying Linear Predictive Coding (LPC) algorithm.Â
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How to Cite
Ranjeeta Kaushik, K. (2014). Speech Parameters Characterization Using Data Mining Techniques. International Journal of Emerging Trends in Science and Technology, 1(06). Retrieved from http://igmpublication.org/ijetst.in/index.php/ijetst/article/view/285
References
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2. John Holmes and Wendy Holmes, “Speech Synthesis and Recognitionâ€, Second Edition, Taylor & Francis Group, New York, 2001, ISBN: 0-7484-0856-8, Ch. 1,4 and 6.
3. Richard L. Klevans and Robert D. Rodman, “Voice Recognitionâ€, Artech House, Inc., MA, 1997, ISBN: 0-890006-927-1, pp 15-31
4. Jerry D. Gibson, Dave Lindbergh ,Toby Berger, Tom Lookabaugh, and Richard L. Baker, “Digital Compression for Multimedia- Principles and Standardsâ€, Morgan Kaufmann Publishers Inc., CA, 1998, ISBN: 1-55860-369-7, pp 1-4 & Ch. 6.
5. Uzdy, Z. , “Human speaker recognition performance of LPC voice processorsâ€, IEEE Transactions on Acoustics, Speech and Signal processing, Vol. 38, Issue 12, 1998
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8. http://www.faqs.org/docs/sp/sp-96.html (Date accessed: 04/24/2010, 05/02/2010)
9. Jeremy Bradbury, Linear Predictive Codingâ€, Dec. 2000 http://my.fit.edu/~vkepuska/ece5525/lpc_paper.pdf
2. John Holmes and Wendy Holmes, “Speech Synthesis and Recognitionâ€, Second Edition, Taylor & Francis Group, New York, 2001, ISBN: 0-7484-0856-8, Ch. 1,4 and 6.
3. Richard L. Klevans and Robert D. Rodman, “Voice Recognitionâ€, Artech House, Inc., MA, 1997, ISBN: 0-890006-927-1, pp 15-31
4. Jerry D. Gibson, Dave Lindbergh ,Toby Berger, Tom Lookabaugh, and Richard L. Baker, “Digital Compression for Multimedia- Principles and Standardsâ€, Morgan Kaufmann Publishers Inc., CA, 1998, ISBN: 1-55860-369-7, pp 1-4 & Ch. 6.
5. Uzdy, Z. , “Human speaker recognition performance of LPC voice processorsâ€, IEEE Transactions on Acoustics, Speech and Signal processing, Vol. 38, Issue 12, 1998
6. Yedlapalli, S.S., “Transforming Real Linear Prediction Coefficients to Line Spectral Representations With a Real FFTâ€, IEEE Transactions on speech and audio processing, Vol. 13, Issue 6, 2005 f
7. http://www.national.com/ds/LM/LM741.pdf D. Roccheso, “Sound Processingâ€
8. http://www.faqs.org/docs/sp/sp-96.html (Date accessed: 04/24/2010, 05/02/2010)
9. Jeremy Bradbury, Linear Predictive Codingâ€, Dec. 2000 http://my.fit.edu/~vkepuska/ece5525/lpc_paper.pdf