Abstract
The processes of measurement, recording and analysis of different sound levels are considered. The amplitude and effect of sound waves vary considerably in continuous space-time measurements. Modeling different types of sounds and their spatiotemporal effects becomes important for assessing the sound situation both in working spaces and in recreation areas. Developing a model that reflects the characteristics of sounds, their sources, and the rules that govern their distribution in different environments would help track sound variations and predict their future changes for spatiotemporal states. Similar works abroad are given, but they are of a private nature. There are many features that you can use to describe audio signals. We consider a wide range of objects to evaluate the effect of each object and select the appropriate set of objects to distinguish between classes. Two estimations of a sound situation are given: on the basis of short-term energy and average speed of change. Three different classification methods are investigated: KNearest neighbors, Gaussian mixture model and Support vector machine.Multi-agent system (M)AS characteristics are given, the classification, trends in the use of multi-agent intelligent technologies for information processing are presented. Authors propose the use of MAS for sound information (MASSI) monitoring. MFSSI structure includes many agents of sound transformation, analysis of information received from them and decision-making. MASSI can handle noise levels in the urban space and to help in the study of noise pollution in many areas.
Highlights
Measuring, registering and analyzing the various levels of sounds and their effect on the surrounding areas is a very complex process
Such a model can represent levels of noise in a large urban space and help in studying noise pollution at various layers: inside a given building, in a specific public park or around the whole city. It shall help in predicting how spatio-temporal chan ges may affect the levels of noise pollution at any of these layers, for instance when a new building complex or a compound community take place in the city
One major issue in building a recognition system for multimedia data is the choice of proper signal features that are likely to result in effective discrimination between different auditory environments
Summary
Belarusian state University of Informatics and Radioelectronics, Minsk, Republic of Belarus. The processes of measurement, recording and analysis of different sound levels are considered. The amplitude and effect of sound waves vary considerably in continuous space-time measurements. Modeling different types of sounds and their spatiotemporal effects becomes important for assessing the sound situation both in working spaces and in recreation areas. Developing a model that reflects the characteristics of sounds, their sources, and the rules that govern their distribution in different environments would help track sound variations and predict their future changes for spatiotemporal states. Multi-agent system (M)AS characteristics are given, the classification, trends in the use of multi-agent intelligent technologies for information processing are presented. Authors propose the use of MAS for sound information (MASSI) monitoring. MASSI can handle noise levels in the urban space and to help in the study of noise pollution in many areas
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