scholarly journals Estimation of Reverberation Time in Classrooms Using the Residual Minimization Method

2017 ◽  
Vol 42 (4) ◽  
pp. 609-617 ◽  
Author(s):  
Artur Nowoświat ◽  
Marcelina Olechowska

Abstract The objective of the residual minimization method is to determine a coefficient correcting the Sabine’s model. The Sabine’s equation is the most commonly applied formula in the designing process of room acoustics with the use of analytical methods. The correction of this model is indispensable for its application in rooms having non-diffusive acoustic field. The authors of the present paper will be using the residual minimization method to work out a suitable correction to be applied for classrooms. For this purpose, five different poorly dampened classrooms were selected, in which the measurements of reverberation time were carried out, and for which reverberation time was calculated with the use of theoretical methods. Three of the selected classrooms had the cubic volume of 258.5 m3 and the remaining two had the cubic volume of 190.8 m3. It was sufficient to estimate the correction for the Sabine’s equation. To verify the results, three other classrooms were selected, in which also the measurements of reverberation time were carried out. The results were verified by means of real measurements of reverberation time and by means of computer simulations in the program ODEON.

2016 ◽  
Vol 106 ◽  
pp. 42-50 ◽  
Author(s):  
Artur Nowoświat ◽  
Marcelina Olechowska ◽  
Jan Ślusarek

Author(s):  
Heather L. Lai ◽  
Brian Hamilton

Abstract This paper investigates the use of two room acoustics metrics designed to evaluate the degree to which the linearity assumptions of the energy density curves are valid. The study focuses on measured and computer-modeled energy density curves derived from the room impulse response of a space exhibiting a highly non-diffuse sound field due to flutter echo. In conjunction with acoustical remediation, room impulse response measurements were taken before and after the installation of the acoustical panels. A very dramatic decrease in the reverberation time was experienced due to the addition of the acoustical panels. The two non-linearity metrics used in this study are the non-linearity parameter and the curvature. These metrics are calculated from the energy decay curves computed per octave band, based on the definitions presented in ISO 3382-2. The non-linearity parameter quantifies the deviation of the EDC from a straight line fit used to generated T20 and T30 reverberation times. Where the reverberation times are calculated based on a linear regression of the data relating to either −5 to −25 dB for T20 or −5 to −35 dB for T30 reverberation time calculations. This deviation is quantified using the correlation coefficient between the energy decay curve and the linear regression for the specified data. In order to graphically demonstrate these non-linearity metrics, the energy decay curves are plotted along with the linear regression curves for the T20 and T30 reverberation time for both the measured data and two different room acoustics computer-modeling techniques, geometric acoustics modeling and finite-difference wave-based modeling. The intent of plotting these curves together is to demonstrate the relationship between these metrics and the energy decay curve, and to evaluate their use for quantifying degree of non-linearity in non-diffuse sound fields. Observations of these graphical representations are used to evaluate the accuracy of reverberation time estimations in non-diffuse environments, and to evaluate the use of these non-linearity parameters for comparison of different computer-modeling techniques or room configurations. Using these techniques, the non-linearity parameter based on both T20 and T30 linear regression curves and the curvature parameter were calculated over 250–4000 Hz octave bands for the measured and computer-modeled room impulse response curves at two different locations and two different room configurations. Observations of these calculated results are used to evaluate the consistency of these metrics, and the application of these metrics to quantifying the degree of non-linearity of the energy decay curve derived from a non-diffuse sound field. These calculated values are also used to evaluate the differences in the degree of diffusivity between the measured and computer-modeled room impulse response. Acoustical computer modeling is often based on geometrical acoustics using ray-tracing and image-source algorithms, however, in non-diffuse sound fields, wave based methods are often able to better model the characteristic sound wave patterns that are developed. It is of interest to study whether these improvements in the wave based computer-modeling are also reflected in the non-linearity parameter calculations. The results showed that these metrics provide an effective criteria for identifying non-linearity in the energy decay curve, however for highly non-diffuse sound fields, the resulting values were found to be very sensitive to fluctuations in the energy decay curves and therefore, contain inconsistencies due to these differences.


2016 ◽  
Vol 139 (4) ◽  
pp. 1980-1980
Author(s):  
Pasquale Bottalico ◽  
Simone Graetzer ◽  
Eric J. Hunter

2012 ◽  
Vol 2012 ◽  
pp. 1-15
Author(s):  
Hui-Qiang Ma ◽  
Nan-Jing Huang

We consider the expected residual minimization method for a class of stochastic quasivariational inequality problems (SQVIP). The regularized gap function for quasivariational inequality problem (QVIP) is in general not differentiable. We first show that the regularized gap function is differentiable and convex for a class of QVIPs under some suitable conditions. Then, we reformulate SQVIP as a deterministic minimization problem that minimizes the expected residual of the regularized gap function and solve it by sample average approximation (SAA) method. Finally, we investigate the limiting behavior of the optimal solutions and stationary points.


1997 ◽  
Vol 4 (4) ◽  
pp. 229-246 ◽  
Author(s):  
Michael Vorländer

In the last decade computer simulations of sound fields in rooms have been developed for application in research and consulting. Some programs are commercially available. Most computer models are based on geometrical room acoustics and/or on statistical (radiosity) methods, thus not including wave phenomena such as diffraction. The uncertainty of typical simulation software was investigated in an international verification test in 1994 and 1995. The results were partly promising although some programs were not as reliable as the operators expected. These round robin tests have been continued until today with simulations and measurements in a concert hall in Jönköping in Sweden. In this paper the basic algorithms of room acoustical computer simulations, the verification in round robin tests and the observed accuracy and limitations are summarised. Finally, possible improvements are discussed.


2021 ◽  
Vol 7 ◽  
Author(s):  
Tomás Sierra-Polanco ◽  
Lady Catherine Cantor-Cutiva ◽  
Eric J. Hunter ◽  
Pasquale Bottalico

The physical production of speech level dynamic range is directly affected by the physiological features of the speaker such as vocal tract size and lung capacity; however, the regulation of these production systems is affected by the perception of the communication environment and auditory feedback. The current study examined the effects of room acoustics in an artificial setting on voice production in terms of sound pressure level and the relationship with the perceived vocal comfort and vocal control. Three independent room acoustic parameters were considered: gain (alteration of the sidetone or playback of one’s own voice), reverberation time, and background noise. An increase in the sidetone led to a decrease in vocal sound pressure levels, thus increasing vocal comfort and vocal control. This effect was consistent in the different reverberation times considered. Mid-range reverberation times (T30 ≈ 1.3 s) led to a decrease in vocal sound pressure level along with an increase in vocal comfort and vocal control, however, the effect of the reverberation time was smaller than the effect of the gain. The presence of noise amplified the aforementioned effects for the variables analyzed.


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