Advanced Time-Frequency Representation in Voice Signal Analysis
| 1 | The State School of Higher Education,
The Institute of Technical Sciences and Aviation,
54 Pocztowa Street, 22-100 Chełm, Poland |
| 2 | Lublin University of Technology, Mechanical Engineering Faculty, Department of Production Engineering, 36 Nadbystrzycka Street, 20-618 Lublin, Poland |
CORRESPONDING AUTHOR
Jerzy Józwik
Lublin University of Technology, Mechanical Engineering Faculty, Department of Production Engineering, 36 Nadbystrzycka Street, 20-618 Lublin, Poland
Lublin University of Technology, Mechanical Engineering Faculty, Department of Production Engineering, 36 Nadbystrzycka Street, 20-618 Lublin, Poland
Publication date: 2018-03-01
Adv. Sci. Technol. Res. J. 2018; 12(1):251–259
KEYWORDS
signal analysisspectrogramtime-frequency representationCohen's classWigner-Ville'a distributiontime-frequency analysis
TOPICS
ABSTRACT
The most commonly used time-frequency representation of the analysis in voice signal is spectrogram. This representation belongs in general to Cohen's class, the class of time-frequency energy distributions. From the standpoint of properties of the resolution spectrogram representation is not optimal. In Cohen class representations are known which have a better resolution properties. All of them are created by smoothing the Wigner-Ville'a (WVD) distribution characterized by the best resolution, however, the biggest harmful interference. Used smoothing functions decide about a compromise between the properties of resolution and eliminating harmful interference term. Another class of time-frequency energy distributions is the affine class of distributions. From the point of view of readability of analysis the best properties are known so called Redistribution of energy caused by the use of a general methodology referred to as reassignment to any time-frequency representation. Reassigned distributions efficiently combine a reduction of the interference terms provided by a well adapted smoothing kernel and an increased concentration of the signal components.
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