KURTOSIS AND NORMALIZED VARIANCE AS MEASURES OF SPEECH SIGNALS CLIPPING VALUE

Authors

  • A. М. Prodeus National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”
  • I. V. Kotvytskyi National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”
  • M. V. Didkovska National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”
  • K. A. Kukharicheva National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”

DOI:

https://doi.org/10.18372/1990-5548.62.14378

Keywords:

Сlipped speech, speech quality, clipping value, kurtosis, normalized variance, matching map

Abstract

It is shown that the kurtosis and the normalized variance can be used as a measures of the clipping value of speech signals. The use of the proposed measures makes it possible to significantly simplify and speed up the clipping value calculations compare to the methods where preliminarily estimation of the probability density function of the analyzed speech signal is required. Subjective estimates of the clipped speech signals quality were obtained. Matching maps between the proposed objective measures and the subjective estimates of the clipped speech signals quality have been built. It was shown that the maps can be well approximated by polynomials of small (1st–4th) order. This fact indicates the possibility of construction of simple, in computational sense, algorithms for the control of clipped speech signals quality.

Author Biographies

A. М. Prodeus, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”

Acoustics and Electroacoustics Department

Doctor of Engineering Science. Professor

orcid.org/0000-0001-7640-0850

I. V. Kotvytskyi, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”

Acoustics and Electroacoustics Department

Postgraduate student

M. V. Didkovska, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”

Department of Mathematical Methods of System Analysis

Candidate of Science (Engineering). Associate Professor

K. A. Kukharicheva, National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”

Acoustics and Electroacoustics Department

Postgraduate student

References

G. R. Avanesjan, Method and device for estimating and indicating distortions of output signal of audio frequency amplifiers (overload indication), Patent RU 2274868 C2, Int.Cl. G01R 23/20, G01R 19/165, 2006.

X. Liu, J. Jia, and L. Cai, “SNR estimation for clipped audio based on amplitude distribution,” Proc. of the 9th Int. Conf. on Natural Computation (ICNC), July 2013. DOI: 10.1109/ICNC.2013.6818205.

S. Aleinik, Yu. Matveev, and A. Raev, “Method of Evaluation of Speech signal clipping level,” Scientific and Technical Journal of Information Technologies, Mechanics and Optics, vol. 79, no. 3, pp. 79–83, 2012. (in Russian).

S. V. Aleinik, Yu. N. Matveev, and A. V. Sholokhov, "Detection of clipped fragments in acoustic signals," Scientific and Technical Journal of Information Technologies, Mechanics and Optics, no. 4 (92), pp. 91–97, 2014.

T. Otani, M. Tanaka, Y. Ota, and S. Ito, Clipping detection device and method, Patent US 8,392,199 B2, Int.Cl. G10 19/00, 2013.

A. Poorjam, J. Jensen, M. Little, and M. Christensen, "Dominant Distortion Classification for Pre-Processing of Vowels in Remote Biomedical Voice Analysis," INTERSPEECH 2017, pp. 289–293, August 20–24, 2017, Stockholm, Sweden. DOI: 10.21437/Interspeech.2017-378

F. Bie, D. Wang, J. Wang, and T. F. Zheng, "Detection and reconstruction of clipped speech for speaker recognition," Speech Communication, vol. 72, pp. 218–231, September 2015. DOI: 10.1016/j.specom.2015.06.008.

C. Laguna and A. Lerch, "An efficient algorithm for clipping detection and declipping audio," AES 141st Convention, 2016, September 29–October 2, Los Angeles, USA.

M. Kendall and A. Stuart, The Advanced Theory of Statistics: Distribution theory. Wiley, 2010.

A. M. Prodeus, I. V. Kotvytskyi, and A. A. Ditiashov, "Assessment of clipped speech quality," Electronics and Control Systems, no. 4(58), pp. 11–18, 2018. DOI:10.18372/1990-5548.58.13504

J. J. A. Moors, "The Meaning of Kurtosis: Darlington Reexamined," The American Statistician, no. 40:4, pp. 283–284, 1986.

V. Arora, and R. Kumar, "Probability distribution estimation of music signals in time and frequency," Proc. of the 19th Int. Conf. on Digital Signal Processing (DSP-2014), pp. 409–414, 20-23 August 2014, Hong Kong.

N. Cote, Integral and diagnostic intrusive prediction of speech. Springer-Verlag: Berlin, Heidelberg, 2011.

A. Prodeus, I. Kotvytskyi, and A. Ditiashov, "Clipped Speech Signals Quality Estimation," Proc. of 5th Int. Conf. “Methods and Systems of Navigation and Motion Control” (MSNMC-2018), pp. 151–155, October 16-18, 2018, Kyiv, Ukraine, ISBN: 978-1-5386-5869-7. DOI: 10.1109/MSNMC.2018.8576308.

Downloads

Issue

Section

THEORY AND METHODS OF SIGNAL PROCESSING