Speech Evaluation System Based on MFCC

Na Wang

doi:10.4028/www.scientific.net/AMR.468-471.2998

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 468-471Speech Evaluation System Based on MFCC

Speech Evaluation System Based on MFCC

Abstract:

In order to evaluate the speaker's pronunciation quality, a speech evaluation system based on MFCC is designed by using some techniques including pre-processing, feature extraction and pattern matching and so on. The MFCC parameters of the standard speech and those of the original speech are extracted. The result is given by the mechanism. Experimental results show that the scores assessed by the system is relating to people’s subjective feeling closely. The software is developed by VC++ and runs on windows XP.

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Periodical:

Advanced Materials Research (Volumes 468-471)

Pages:

2998-3001

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.468-471.2998

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Online since:

February 2012

Authors:

Na Wang

Keywords:

Dynamic Time Warping, Feature Extraction, Mel-Frequency Cepstral Coefficients (MFCC), Speech Evaluation

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References

[1] S.M. Witt, S.J. Young: Phone-level Pronunciation Scoring and Assessment for Interactive Language Learning. in:Speech Communication 30(2000), p.95

DOI: 10.1016/s0167-6393(99)00044-8

Google Scholar

[2] JiangChun Chen, J.R. Jang,Junyi Li and MingChun Wu:Automatic pronunciation assessment for Mandarin Chinese. In Proceedings of ICME(2004), p.(1979)

Google Scholar

[3] Minhua Li, Ruwei Dai,Yaodong Li: Pattern Recognition and Artificial Intelligence.In Chinese.Vol.21(2008), p.469

Google Scholar

[4] J. Gros, F. Mihelic, N. Pavesic, in:Proceedings of ISIE.Vol.1(1999),P.213

Google Scholar

[5] Weixia Li, Robert F. Kubichek.Output-based objective speech quality measurement using continuous hidden Markov models,in: Seventh International Symposium on Signal Processing and Its Applications( 2003),p.389

DOI: 10.1109/isspa.2003.1224722

Google Scholar

[6] C.H. Lee, C.H. Chou, C.C. Han, and R.Z. Huang, in:Pattern Recogn.Lett.Vol.27(2006),p.93

Google Scholar

[7] S. Davis,P. Mermelstein, in: Acoustics, Speech and Signal Processing.Vol.28(1980), p.357

Google Scholar

[8] O.B. Tuzun, M. Demirekler, K.B. Nakiboglu, in: Proceedings of MELECON. Mediterranean Electrotechnical Conference(1994),p.65

DOI: 10.1109/melcon.1994.381143

Google Scholar

[9] F. G. Hashad, T. M. Halim, S. M. Diab, and B. M. Sallam.A new approach for fingerprint recognition based on mel frequency cepstral coefficients. In ICCES (2009), p.263

DOI: 10.1109/icces.2009.5383272

Google Scholar

[10] P.Tormene, T.Giorgino, S. Quaglini and M.Stefanelli, in:Artif Intell Med.Vol. 45(2009),p.11

Google Scholar

[11] Junyi Li:Speech Evaluation.In Chinese.TW(2002).

Google Scholar