Computer investigations of sound perception and noise annoyance

• Autorzy: Ossowski A. , Smyrnova Y.
• Języki publikacji: EN

Abstrakty

EN

The problem of influence of adverse sound environments on human psychophysical state and health has been outlined. Basic sound characteristics have been defined and the fundamental question of the relation between subjective and objective characteristics has been formulated. The general conception of a computer system for studying human perception of environmental sound and noise has been described. The usefulness of application of data mining algorithms in order to find practical rules that enable to determine subjective sound and noise parameters from the knowledge of physical ones has been pointed out.

Słowa kluczowe

EN

psychoacoustics; sound characteristics correlation; data mining; rules in data bases

PL

psychoakustyka; korelacja dźwięku; eksploracja danych; zasady w bazach danych

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2001
• Tom: Vol. 2, Part. 2
• Strony: SN27--SN32
• Opis fizyczny: Bibliogr. 10 poz., rys.

Twórcy

autor

Ossowski A.

• Institute of Fundamental Technological Research PAS, 00-049 Warszawa, ul. Świętokrzyska 21

autor

Smyrnova Y.

• Institute of Fundamental Technological Research PAS, 00-049 Warszawa, ul. Świętokrzyska 21

Bibliografia

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• [3] PREIS A.., Noise Annoyance and its components, Centre for sensory Research, Stockholm, 1995.
• [4] BENDAT J., Random data: Analysis and measurement procedures, Wiley-Interscience, New York, 1971.
• [5] ZWICKER E., FASTL H., Psychoacoustics-Facts and models, Heidelberg, Germany, 1990.
• [6] STEVENS S., Psychophysics. Introduction to its perceptual, neural and social prospects, Wiley, New York, 1975.
• [7] KRYTER K., The effects of noise on man, Academic press, London, 1985.
• [8] BISMARK G., Sharpness as a attribute of the timbre of steady sound, Acustica, Vol. 58, pp. 268-280, Germany, 1985.
• [9] KLIR G., Fuzzy sets, uncertainty and information, Englenood Cliffs Prentice-hall, 1988.
• [10] PLAZA R., LOPEZ de MANTARAS, A case-base apprentice that learns from fuzzy examples, Proc of the 5th Int, Symp. on Methodologies for Intelligent Systems, pp. 420-427, 1990.