About: Annoyance is a(n) research topic. Over the lifetime, 2015 publication(s) have been published within this topic receiving 38300 citation(s). The topic is also known as: annoy.
Papers published on a yearly basis
TL;DR: There is sufficient scientific evidence that noise exposure can induce hearing impairment, hypertension and ischemic heart disease, annoyance, sleep disturbance, and decreased school performance, which implies that in the twenty-first century noise exposure will still be a major public health problem.
Abstract: Exposure to noise constitutes a health risk. There is sufficient scientific evidence that noise exposure can induce hearing impairment, hypertension and ischemic heart disease, annoyance, sleep disturbance, and decreased school performance. For other effects such as changes in the immune system and birth defects, the evidence is limited. Most public health impacts of noise were already identified in the 1960s and noise abatement is less of a scientific but primarily a policy problem. A subject for further research is the elucidation of the mechanisms underlying noise-induced cardiovascular disorders and the relationship of noise with annoyance and nonacoustical factors modifying health outcomes. A high priority study subject is the effects of noise on children, including cognitive effects and their reversibility. Noise exposure is on the increase, especially in the general living environment, both in industrialized nations and in developing world regions. This implies that in the twenty-first century noise exposure will still be a major public health problem.
TL;DR: Better estimates of the confidence intervals due to the improved model of the relationship between annoyance and noise exposure are provided, which is easier to use for practical calculations than the model itself.
Abstract: We present a model of the distribution of noise annoyance with the mean varying as a function of the noise exposure. Day-night level (DNL) and day-evening-night level (DENL) were used as noise descriptors. Because the entire annoyace distribution has been modeled, any annoyance measure that summarizes this distribution can be calculated from the model. We fitted the model to data from noise annoyance studies for aircraft, road traffic, and railways separately. Polynomial approximations of relationships implied by the model for the combinations of the following exposure and annoyance measures are presented: DNL or DENL, and percentage "highly annoyed" (cutoff at 72 on a scale of 0-100), percentage "annoyed" (cutoff at 50 on a scale of 0-100), or percentage (at least) "a little annoyed" (cutoff at 28 on a scale of 0-100). These approximations are very good, and they are easier to use for practical calculations than the model itself, because the model involves a normal distribution. Our results are based on the same data set that was used earlier to establish relationships between DNL and percentage highly annoyed. In this paper we provide better estimates of the confidence intervals due to the improved model of the relationship between annoyance and noise exposure. Moreover, relationships using descriptors other than DNL and percentage highly annoyed, which are presented here, have not been established earlier on the basis of a large dataset.
TL;DR: It is proposed that the average of these curves is the best currently available relationship for predicting community annoyance due to transportation noise of all kinds.
Abstract: Since noise was first recognized as a serious environmental pollutant, a number of social surveys have been conducted in order to assess the magnitude of the problem and to develop suitable noise ratings, such that, from a measurement of certain physical characteristics of community noise, one could reliably predict the community’s subjective response to the noise. Recently, the author has reviewed the data from social surveys concerning the noise of aircraft, street traffic, expressway traffic, and railroads. Going back to the original published data, the various survey noise ratings were translated to day–night average sound level, and an independent judgment was made, where choice was possible, as to which respondents should be counted as ’’highly annoyed.’’ The results of 11 of these surveys show a remarkable consistency. It is proposed that the average of these curves is the best currently available relationship for predicting community annoyance due to transportation noise of all kinds.
04 Jun 2005-The Lancet
TL;DR: The findings indicate that a chronic environmental stressor-aircraft noise-could impair cognitive development in children, specifically reading comprehension, and schools exposed to high levels of aircraft noise are not healthy educational environments.
Abstract: Methods We did a cross-national, cross-sectional study in which we assessed 2844 of 3207 children aged 9-10 years who were attending 89 schools of 77 approached in the Netherlands, 27 in Spain, and 30 in the UK located in local authority areas around three major airports. We selected children by extent of exposure to external aircraft and road traffic noise at school as predicted from noise contour maps, modelling, and on-site measurements, and matched schools within countries for socioeconomic status. We measured cognitive and health outcomes with standardised tests and questionnaires administered in the classroom. We also used a questionnaire to obtain information from parents about socioeconomic status, their education, and ethnic origin. Findings We identified linear exposure-effect associations between exposure to chronic aircraft noise and impairment of reading comprehension (p=0·0097) and recognition memory (p=0·0141), and a non-linear association with annoyance (p� 0·0001) maintained after adjustment for mother's education, socioeconomic status, longstanding illness, and extent of classroom insulation against noise. Exposure to road traffic noise was linearly associated with increases in episodic memory (conceptual recall: p=0·0066; information recall: p=0·0489), but also with annoyance (p=0·0047). Neither aircraft noise nor traffic noise affected sustained attention, self-reported health, or overall mental health.
01 Jan 2002
TL;DR: Results show that a prosodic model can predict whether an utterance is neutral ve sus “annoyed or frustrated” with an accuracy on par with that of human interlabeler agreement.
Abstract: We investigate the use of prosody for the detection of frustr ation and annoyance in natural human-computer dialog. In addition to prosodic features, we examine the contribution of language model information and speaking “style”. Results show that a prosodic model can predict whether an utterance is neutral ve sus “annoyed or frustrated” with an accuracy on par with that of human interlabeler agreement. Accuracy increases when dis criminating only “frustrated” from other utterances, and when u sing only those utterances on which labelers originally agreed. Furthermore, prosodic model accuracy degrades only slightly when u si g recognized versus true words. Language model features, eve n if based on true words, are relatively poor predictors of frust ration. Finally, we find that hyperarticulation is not a good predict or of emotion; the two phenomena often occur independently.
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