Analysis of the influence of signal compression techniques for voice disorder detection through filter-banked based features
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Dec 19, 2015
Published:
Nov 7, 2015
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Abstract
This paper compares the results of using compressed voice signals versus uncompressed speech signals to automatically detect voice abnormalities. Coding techniques and voice compression used in this study are the same as those used by default in the fixed, mobile and ip telephony systems, and techniques of characterization and classification used are also among the most used for detecting automatic speech abnormalities. The results obtained indicate that it is possible to use compressed voice signals for automatic detection of vocal pathologies without compromising the success rate in the diagnosis, which would make the implementation of automatic remote diagnosis of vocal pathologies possible.
How to Cite
Sepúlveda Cano, L. M., Quiza Montealegre, J. J., & Gómez García, J. A. (2015). Analysis of the influence of signal compression techniques for voice disorder detection through filter-banked based features. Revista Ingenierías Universidad De Medellín, 16(30), 49–66. https://doi.org/10.22395/rium.v16n30a3
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References
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[3] I. Otung, Communication engineering principles: Palgrave Macmillan, 2001.
[4] B. Sklar, Digital communications vol. 2: Prentice Hall NJ, 2001.
[5] T. ITU, "Recommendation G. 711," Pulse Code Modulation (PCM) of voice frequencies, November, 1988.
[6] R. ITU-T and I. Recommend, "P. 800," Methods for subjective determination of transmission quality, 1996.
[7] S. Haykin, Communication systems: John Wiley & Sons, 2008.
[8] J. Davidson, Voice over IP fundamentals: Cisco press, 2006.
[9] D. Peña, Análisis de datos multivariantes vol. 24: McGraw-Hill Madrid, 2002.
[10] J. B. Alonso, et al., "Automatic detection of pathologies in the voice by HOS based parameters," EURASIP Journal on Applied Signal Processing, vol. 4, pp. 275-284, 2001.
[11] G. Banci, et al., "Vocal fold disorder evaluation by digital speech analysis," Journal of Phonetics, vol. 14, pp. 495-499, 1986.
[12] B. Boyanov and S. Hadjitodorov, "Acoustic analysis of pathological voices. A voice analysis system for the screening of laryngeal diseases," Engineering in Medicine and Biology Magazine, IEEE, vol. 16, pp. 74-82, 1997.
[13] A. A. Dibazar, et al., "Feature analysis for automatic detection of pathological speech," in Engineering in Medicine and Biology, 2002. 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society EMBS/BMES Conference, 2002. Proceedings of the Second Joint, 2002, pp. 182-183 vol.1.
[14] M. K. Arjmandi and M. Pooyan, "An optimum algorithm in pathological voice quality assessment using wavelet-packet-based features, linear discriminant analysis and support vector machine," Biomedical Signal Processing and Control, vol. 7, pp. 3-19, 2012.
[15] R. J. Moran, et al., "Telephony-based voice pathology assessment using automated speech analysis," Biomedical Engineering, IEEE Transactions on, vol. 53, pp. 468-477, 2006.
[16] M. F. Kaleem, et al., "Telephone-quality pathological speech classification using empirical mode decomposition," in Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE, 2011, pp. 7095-7098.
[17] N. Saenz-Lechon, et al., "Effects of Audio Compression in Automatic Detection of Voice Pathologies," Biomedical Engineering, IEEE Transactions on, vol. 55, pp. 2831-2835, 2008.
[18] D. Arifianto, "Enhancement of speech over wireless network using sinusoidal modeling and synthesis," in Signal Processing Systems (SiPS), 2013 IEEE Workshop on, 2013, pp. 301-305.
[19] V. Uloza, et al., "Exploring the feasibility of smart phone microphone for measurement of acoustic voice parameters and voice pathology screening," European Archives of Oto-Rhino-Laryngology, pp. 1-9, 2015/07/11 2015.
[20] M. Eye and E. Infirmary, "Voice disorders database, version. 1.03 (cd-rom)," Lincoln Park, NJ: Kay Elemetrics Corporation, 1994.
[21] G. Smillie, Analogue and digital communication techniques: Butterworth-Heinemann, 1999.
[22] S. Karapantazis and F.-N. Pavlidou, "VoIP: A comprehensive survey on a promising technology," Computer Networks, vol. 53, pp. 2050-2090, 2009.
[23] A. R. Madane, et al., "Speech compression using Linear predictive coding," in proceedings International workshop on Machine Intelligence Research MIR labs, 2009.
[24] M. Hasegawa-Johnson, "Lecture notes in speech production, speech coding, and speech recognition," class notes, University of Illinois at Urbana-Champaign, Fall, 2000.
[25] L. M. Sepúlveda Cano, "Análisis Dinámico de Relevancia en Bioseñales," Universidad Nacional de Colombia-Sede Manizales, 2013.
[26] A. F. Quiceno Manrique, "Análisis tiempo-frecuencia por métodos no paramétricos orientado a la detección de patologías en bioseñales," Universidad Nacional de Colombia-Sede Manizales, 2009.