Annoyance

About: Annoyance is a research topic. Over the lifetime, 2015 publications have been published within this topic receiving 38300 citations. The topic is also known as: annoy.

Generating Membership Functions for a Noise Annoyance Model from Experimental Data

Abstract: The success of fuzzy expert systems could be mainly attributed to the inclusion of linguistic terms into their reasoning scheme. This allows reasoning about complex issues within a certain (tolerated) degree of imprecision. Hence, an important issue in the development of such systems is the choice of the membership functions that model the linguistic terms involved in the application. In this chapter we will describe several methods for the construction of these membership functions (which represent information) from measurements obtained in psycholinguistic experiments. Special attention will be paid to the inclusive and the non-inclusive interpretation of linguistic terms. Secondly, these techniques are applied to data gathered in an International Annoyance Scaling Study, where the relationship between more than 20 different linguistic terms and their corresponding noise annoyance level was under survey.

A two-week monitoring of self-reported arousal, worry and attribution among persons with annoyance attributed to electrical equipment and smells.

Abstract: Non-patients attributing annoyance to either smells (smell annoyed; SA, n= 29) or electrical equipment (electrically annoyed; EA, n= 17), or both (generally annoyed; GA, n= 38), were monitored for 2 weeks through daily self-ratings of arousal (stress), sleep disturbances, health complaints, worry about hypersensitivity reactions, avoidance behaviors, and attributions of health complaints to electrical equipment and smells. In parallel, a demographically matched reference group was followed (n= 56). GA persons reported higher arousal (stress), more subjective health complaints, and more sleep disturbances than the other groups. About 60% in the GA and EA groups reported intentional avoidance behavior, compared to 31% in the SA group and 2% of the referents. Worry and attribution to environmental factors was also more frequent among GA persons than in the other groups. Thus, even at sub-clinical levels, environmental annoyance generalized to several triggers seems to be associated with behaviors commonly observed among patients with idiopathic environmental intolerance.

Annoyance of individual artifacts in MPEG-2 compressed video and their relation to overall annoyance

Abstract: In this work we describe a study on a limited number of artifacts in MPEG-2 compressed video with the primary aim to analyze how annoying these compression artifacts are. More specifically, the objectives were: (1) to determine how the subjective annoyances of individual artifacts contribute to the overall annoyance, (2) to obtain the subjective ranks of the artifacts, and (3) to determine what relationships exist between annoyance values and annoyance ranks. To this end, a psychophysical experiment was carried out in which observers provided us with their subjective assessment of video sequences. The results showed that at low compression bit-rates, the blocking artifacts were the most annoying, whereas at higher compression bit-rates the ringing artifacts were the most annoying. The blocking artifact had the highest mean annoyance rank across all videos and compression bit-rates. Mean annoyance values were ordered differently from mean annoyance ranks due to very high annoyance values associated with some artifacts. Overall annoyance was related to the total squared error by a Logistic function. Individual artifact annoyance was related to overall annoyance by a weighted Minkowski metric.

Influence of temporal structure of the sonic environment on annoyance

Abstract: The relationship between environmental noise exposure and annoyance has been well-investigated and well-documented, insofar that the European Commission includes estimated annoyance as an evaluation measure for the impact of noise exposure (2002-49-EC). Although exposure-effect relationships for different sources have been generally accepted, the uncertainty in these models remains substantial (Marquis-Favre et al. 2005; Fields et al. 2000) for example have calculated that the response between communities differs on average by the equivalent of about 7 dB in noise exposure. One major issue here is the contribution of non-acoustical factors (Fields 1993) and another the uncertainty of the exposure modeling method (Lercher et al. 2008b).