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一项针对中学教师嗓音参数及教室声学影响的一学年纵向研究。

A one-school year longitudinal study of secondary school teachers' voice parameters and the influence of classroom acoustics.

作者信息

Calosso Giulia, Puglisi Giuseppina Emma, Astolfi Arianna, Castellana Antonella, Carullo Alessio, Pellerey Franco

机构信息

Department of Energy Corso Duca degli Abruzzi, 24, Politecnico di Torino, Torino, 10129, Italy.

Department of Electronics and Telecommunications Corso Duca degli Abruzzi, 24, Politecnico di Torino, Torino, 10129, Italy.

出版信息

J Acoust Soc Am. 2017 Aug;142(2):1055. doi: 10.1121/1.4998707.

Abstract

Recent literature reports that a large percentage of teachers complain that teaching has an adverse effect on their voice status. Thus, more needs to be done to study their vocal behavior. The objective of this longitudinal study was twofold: to determine changes in the voice use of teachers over a school year, and to study the relationships between voice use and classroom acoustic parameters. Thirty-one teachers from two secondary schools in Turin (Italy) were involved at the beginning of the 2014-2015 school year, and 22 of them also participated at the end of the same school year. The results show that teachers adjust their voices with noise and reverberation. A minimum value of the sound pressure level of voice (SPL) was found at a mid-frequency reverberation time of 0.8 s in both periods. Moreover, the teachers who worked in the worst classroom acoustic conditions showed an increase of 2.3 dB in the mean SPL and a decrease of 10% in the voicing time percentage at the end of the school year. A predictive model that can be used to estimate the mean SPL from the background noise level and the reverberation time, based on collected data, is here proposed.

摘要

近期文献报道,很大比例的教师抱怨教学对他们的嗓音状况有不利影响。因此,需要做更多研究来探究他们的发声行为。这项纵向研究的目的有两个:一是确定教师在一学年中嗓音使用情况的变化,二是研究嗓音使用与教室声学参数之间的关系。2014 - 2015学年开始时,来自意大利都灵两所中学的31名教师参与其中,其中22名教师在同一学年结束时也继续参与。结果表明,教师会根据噪音和混响来调整他们的嗓音。在两个时间段中,当混响时间为0.8秒的中频时,发现嗓音声压级(SPL)有最小值。此外,在教室声学条件最差的环境中工作的教师,在学年末平均声压级增加了2.3分贝,发声时间百分比下降了10%。基于收集的数据,本文提出了一个预测模型,该模型可用于根据背景噪音水平和混响时间来估计平均声压级。

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