Method for Measuring the Intelligibility of Speech Signals in the Kullback–Leibler Information Metric

• Published in: Measurement techniques 2019-12, Vol.62 (9), p.832-839
• Main Authors: Savchenko, V. V., Savchenko, L. V.
• Format: Article
• Language: English
• Subjects: Analytical Chemistry; Characterization and Evaluation of Materials; Intelligibility; Measurement Science and Instrumentation; Physical Chemistry; Physics; Physics and Astronomy; Real time operation; Regression analysis; Regression models; Speech; Speech processing; Speech recognition
• ISSN: 0543-1972; 1573-8906
• DOI: 10.1007/s11018-019-01702-1

We consider the problem of determination of the intelligibility of speech of a speaker according to a finite fragment of the speech signal. It is shown that the main difficulties in the solution of this problem are connected with the necessity of analysis of small samples. To overcome the problem of small samples, we proposed a new high-speed method for measuring the intelligibility of speech signals on the sonic level of its perception. The proposed method is based on the information indicator of speech intelligibility in the Kullback-Leibler metric. We consider an example of practical realization of the new method with the use of a self-regression model of minimum sound units from the speech flow of a speaker. The characteristics of efficiency of the new method are analyzed. It is shown that, under certain conditions, the application of the information indicator enables us to realize the general systems principle of guaranteed result. On the basis of the software developed by the authors, we designed and performed full-scale experiments and established quantitative estimates for the speed of this method. It is shown that, with the help of this method, quite accurate and reliable estimates of the information indicator are obtained for short (2–3 min) segments of speech signals. The accumulated results and the conclusions made on their basis are intended for applications in the development of new systems and improvement of the existing systems of automatic speech processing and recognition intended for the operation in the real-time mode.