scholarly journals Measurements of Acoustical Parameters in the Ancient Open-Air Theatre of Tyndaris (Sicily, Italy)

2020 ◽  
Vol 10 (16) ◽  
pp. 5680
Author(s):  
Arianna Astolfi ◽  
Elena Bo ◽  
Francesco Aletta ◽  
Louena Shtrepi
Keyword(s):  
Room Acoustics ◽  
Good Reproducibility ◽  
Reverberation Time ◽  
Acoustic Features ◽  
Acoustical Parameters ◽  
Sound Sources ◽  
Research Attention ◽  
Iso Standard ◽  
Measurement Campaign ◽  
Architectural Element

The emerging field of archaeoacoustics is attracting increasing research attention from scholars of different disciplines: the investigation of the acoustic features of ancient open-air theatres is possibly one of its main themes. In this paper, the outcomes of a measurement campaign of acoustical parameters in accordance with ISO 3382-1 in the ancient theatre of Tyndaris (Sicily) are presented and compared with datasets from other sites. Two sound sources were used (firecrackers and dodecahedron) and their differences were analysed. A very good reproducibility has been shown between the two measurement chains, with differences on average of 0.01 s for reverberation time T20, and less than 0.3 dB for Clarity C50 and C80 and for sound strength. In general, results show that the reverberation time and strength of sound values are relatively low when compared with other theatres because of the lack of the original architectural element of the scaenae frons. When combining this effect with the obvious condition of an unroofed space, issues emerge in terms of applicability of the protocols recommended in the ISO standard. This raises the question of whether different room acoustics parameters should be used to characterise open-air ancient theatres.

scholarly journals THE PECULIARITIES OF THE SOUND FIELD ENERGY DECAY IN A ROOM WITH THE USE OF DIFFERENT PULSED SOUND SOURCES/GARSO LAUKO ENERGIJOS SLOPIMO PATALPOJE YPATUMAI, NAUDOJANT SKIRTINGUS IMPULSINIUS GARSO ŠALTINIUS

1999 ◽  
Vol 5 (2) ◽  
pp. 135-140
Author(s):  
Vytautas Stauskis
Keyword(s):  
Noise Level ◽  
Sound Field ◽  
Maximum Energy ◽  
Reverberation Time ◽  
Frequency Range ◽  
Sound Sources ◽  
Low Frequencies ◽  
High Frequencies ◽  
The Difference ◽  
Field Decay

The paper deals with the differences between the energy created by four different pulsed sound sources, ie a sound gun, a start gun, a toy gun, and a hunting gun. A knowledge of the differences between the maximum energy and the minimum energy, or the signal-noise ratio, is necessary to correctly calculate the frequency dependence of reverberation time. It has been established by investigations that the maximum energy excited by the sound gun is within the frequency range of 250 to 2000 Hz. It decreases by about 28 dB at the low frequencies. The character of change in the energy created by the hunting gun differs from that of the sound gun. There is no change in the maximum energy within the frequency range of 63–100 Hz, whereas afterwards it increases with the increase in frequency but only to the limit of 2000 Hz. In the frequency range of 63–500 Hz, the energy excited by the hunting gun is lower by 15–30 dB than that of the sound gun. As frequency increases the difference is reduced and amounts to 5–10 dB. The maximum energy of the start gun is lower by 4–5 dB than that of the hunting gun in the frequency range of up to 1000 Hz, while afterwards the difference is insignificant. In the frequency range of 125–250 Hz, the maximum energy generated by the sound gun exceeds that generated by the hunting gun by 20 dB, that by the start gun by 25 dB, and that by the toy gun—by as much as 35 dB. The maximum energy emitted by it occupies a wide frequency range of 250 to 2000 Hz. Thus, the sound gun has an advantage over the other three sound sources from the point of view of maximum energy. Up until 500 Hz the character of change in the direct sound energy is similar for all types of sources. The maximum energy of direct sound is also created by the sound gun and it increases along with frequency, the maximum values being reached at 500 Hz and 1000 Hz. The maximum energy of the hunting gun in the frequency range of 125—500 Hz is lower by about 20 dB than that of the sound gun, while the maximum energy of the toy gun is lower by about 25 dB. The maximum of the direct sound energy generated by the hunting gun, the start gun and the toy gun is found at high frequencies, ie at 1000 Hz and 2000 Hz, while the sound gun generates the maximum energy at 500 Hz and 1000 Hz. Thus, the best results are obtained when the energy is emitted by the sound gun. When the sound field is generated by the sound gun, the difference between the maximum energy and the noise level is about 35 dB at 63 Hz, while the use of the hunting gun reduces the difference to about 20–22 dB. The start gun emits only small quantities of low frequencies and is not suitable for room's acoustical analysis at 63 Hz. At the frequency of 80 Hz, the difference between the maximum energy and the noise level makes up about 50 dB, when the sound field is generated by the sound gun, and about 27 dB, when it is generated by the hunting gun. When the start gun is used, the difference between the maximum signal and the noise level is as small as 20 dB, which is not sufficient to make a reverberation time analysis correctly. At the frequency of 100 Hz, the difference of about 55 dB between the maximum energy and the noise level is only achieved by the sound gun. The hunting gun, the start gun and the toy gun create the decrease of about 25 dB, which is not sufficient for the calculation of the reverberation time. At the frequency of 125 Hz, a sufficiently large difference in the sound field decay amounting to about 40 dB is created by the sound gun, the hunting gun and the start gun, though the character of the sound field curve decay of the latter is different from the former two. At 250 Hz, the sound gun produces a field decay difference of almost 60 dB, the hunting gun almost 50 dB, the start gun almost 40 dB, and the toy gun about 45 dB. At 500 Hz, the sound field decay is sufficient when any of the four sound sources is used. The energy difference created by the sound gun is as large as 70 dB, by the hunting gun 50 dB, by the start gun 52 dB, and by the toy gun 48 dB. Such energy differences are sufficient for the analysis of acoustic indicators. At the high frequencies of 1000 to 4000 Hz, all the four sound sources used, even the toy gun, produce a good difference of the sound field decay and in all cases it is possible to analyse the reverberation process at varied intervals of the sound level decay.

scholarly journals Separable neural representations of sound sources: Speaker identity and musical timbre

2019 ◽  
Author(s):  
Mattson Ogg ◽  
Dustin Moraczewski ◽  
Stefanie Kuchinsky ◽  
L. Robert Slevc
Keyword(s):  
Signal To Noise Ratio ◽  
Stimulus Presentation ◽  
Machine Intelligence ◽  
Acoustic Features ◽  
Sound Sources ◽  
Temporal Lobes ◽  
Cortical Organization ◽  
Superordinate Category ◽  
Category Labels ◽  
The Many

Human listeners can quickly and easily recognize different sound sources (objects and events) in their environment. Understanding how this impressive ability is accomplished can improve signal processing and machine intelligence applications along with assistive listening technologies. However, it is not clear how the brain represents the many sounds that humans can recognize (such as speech and music) at the level of individual sources, categories and acoustic features. To examine the cortical organization of these representations, we used patterns of fMRI responses to decode 1) four individual speakers and instruments from one another (separately, within each category), 2) the superordinate category labels associated with each stimulus (speech or instrument), and 3) a set of simple synthesized sounds that could be differentiated entirely on their acoustic features. Data were collected using an interleaved silent steady state sequence to increase the temporal signal-to-noise ratio, and mitigate issues with auditory stimulus presentation in fMRI. Largely separable clusters of voxels in the temporal lobes supported the decoding of individual speakers and instruments from other stimuli in the same category. Decoding the superordinate category of each sound was more accurate and involved a larger portion of the temporal lobes. However, these clusters all overlapped with areas that could decode simple, acoustically separable stimuli. Thus, individual sound sources from different sound categories are represented in separate regions of the temporal lobes that are situated within regions implicated in more general acoustic processes. These results bridge an important gap in our understanding of cortical representations of sounds and their acoustics.

Quantifying Non-Linearity in Early Decay Curves of Measured and Computer-Modeled Room Impulse Responses of a Highly Non-Diffuse Room Exhibiting Flutter Echo

2020 ◽  
Author(s):  
Heather L. Lai ◽  
Brian Hamilton
Keyword(s):  
Linear Regression ◽  
Computer Modeling ◽  
Impulse Response ◽  
Decay Curve ◽  
Sound Field ◽  
Energy Decay ◽  
Room Acoustics ◽  
Reverberation Time ◽  
Sound Fields ◽  
Regression Curves

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.

The Physics of Music

2012 ◽  
pp. 29-47
Author(s):  
Jyri Pakarinen
Keyword(s):  
Sound Transmission ◽  
Sound Field ◽  
Room Acoustics ◽  
Human Observer ◽  
Sound Sources ◽  
Acoustic Effect ◽  
Musical Sound ◽  
Transmission Parameters ◽  
Definition Of ◽  
Physical Phenomena

This chapter discusses the central physical phenomena involved in music. The aim is to provide an explanation of the related issues in an understandable level, without delving unnecessarily deep in the underlying mathematics. The chapter is divided in two main sections: musical sound sources and sound transmission to the observer. The first section starts from the definition of sound as wave motion, and then guides the reader through the vibration of strings, bars, membranes, plates, and air columns, that is, the oscillating sources that create the sound for most of the musical instruments. Resonating structures, such as instrument bodies are also reviewed, and the section ends with a discussion on the potential physical markup parameters for musical sound sources. The second section starts with an introduction to the basics of room acoustics, and then explains the acoustic effect that the human observer causes in the sound field. The end of the second section provides a discussion on which sound transmission parameters could be used in a general music markup language. Finally, a concluding section is presented.

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
Keyword(s):  
Computer Simulations ◽  
Acoustic Field ◽  
Analytical Methods ◽  
Room Acoustics ◽  
Reverberation Time ◽  
Minimization Method ◽  
Theoretical Methods ◽  
Residual Minimization

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.

scholarly journals Humans rely on the same rules to assess emotional valence and intensity in conspecific and dog vocalizations

2014 ◽  
Vol 10 (1) ◽  
pp. 20130926 ◽  
Author(s):  
Tamás Faragó ◽  
Attila Andics ◽  
Viktor Devecseri ◽  
Anna Kis ◽  
Márta Gácsi ◽  
...  
Keyword(s):  
Emotional Valence ◽  
Emotional Content ◽  
Acoustic Cues ◽  
Acoustic Features ◽  
Acoustical Parameters ◽  
Intensity Perception ◽  
First Time ◽  
Vocal Expressions

Humans excel at assessing conspecific emotional valence and intensity, based solely on non-verbal vocal bursts that are also common in other mammals. It is not known, however, whether human listeners rely on similar acoustic cues to assess emotional content in conspecific and heterospecific vocalizations, and which acoustical parameters affect their performance. Here, for the first time, we directly compared the emotional valence and intensity perception of dog and human non-verbal vocalizations. We revealed similar relationships between acoustic features and emotional valence and intensity ratings of human and dog vocalizations: those with shorter call lengths were rated as more positive, whereas those with a higher pitch were rated as more intense. Our findings demonstrate that humans rate conspecific emotional vocalizations along basic acoustic rules, and that they apply similar rules when processing dog vocal expressions. This suggests that humans may utilize similar mental mechanisms for recognizing human and heterospecific vocal emotions.

Speech accommodation to room acoustics: Reverberation time and clarity

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

scholarly journals Acoustical Design and Noise Control in Metro Stations: Case Studies of the Ankara Metro System

2007 ◽  
Vol 14 (3) ◽  
pp. 203-221 ◽  
Author(s):  
Zühre Sü ◽  
Mehmet Çalışkan
Keyword(s):  
Computer Simulation ◽  
Nonwoven Material ◽  
Sound Level ◽  
Reverberation Time ◽  
Acoustical Parameters ◽  
Transmission Index ◽  
Speech Transmission ◽  
Absorbing Materials ◽  
Practical Design ◽  
Metro System

The aim of this research is to demonstrate the importance of initial strategies in acoustical design of underground metro stations. The paper searches for practical design solutions by evaluating different materials for providing optimum acoustical conditions in such spaces. Acoustical designs of three metro stations on a new expansion line in Ankara including Sogutozu, Bilkent and ODTU metro stations are presented through computer simulation. Predictions of room acoustical parameters are presented for both platform and ticket office floors in terms of parameters like reverberation time (RT), speech transmission index (STI) and A-weighted sound level (SPL) distribution within spaces. Simulated reverberation times are evaluated in view of legislative requirements. The study confirms the importance of using sound absorbing materials on the ceiling and sidewalls together. The nonwoven material, used behind perforated metal suspended ceilings, has proved effective in reverberation control.

scholarly journals Changes of Voice Production in Artificial Acoustic Environments

2021 ◽  
Vol 7 ◽  
Author(s):  
Tomás Sierra-Polanco ◽  
Lady Catherine Cantor-Cutiva ◽  
Eric J. Hunter ◽  
Pasquale Bottalico
Keyword(s):  
Sound Pressure Level ◽  
Sound Pressure ◽  
Dynamic Range ◽  
Vocal Tract ◽  
Production Systems ◽  
Pressure Level ◽  
Room Acoustics ◽  
Reverberation Time ◽  
Voice Production ◽  
Vocal Control

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.

scholarly journals Aspects regarding the acoustics of a lecture hall

2019 ◽  
Vol XXII (2) ◽  
pp. 268-275
Author(s):  
Pazara T.
Keyword(s):  
Speech Intelligibility ◽  
Great Influence ◽  
Lecture Hall ◽  
Naval Academy ◽  
Reverberation Time ◽  
Acoustical Parameters ◽  
Transmission Index ◽  
Speech Transmission ◽  
Virtual Simulations ◽  
Teaching Conditions

In a lecture hall it is vital to assure proper teaching conditions meaning that the information from the speaker/teacher must be received correctly by the listeners. Speech intelligibility is the main objective when a lecture hall is evaluated. In this paper, the authors discuss the importance of the acoustics of a lecture hall and the influence of various parameters over speech transmission from the speaker – the professors to the listeners – the students. The number of acoustical parameters is very large, but Speech Transmission Index (STI) and Reverberation Time (RT) are commonly used to evaluate the acoustics of a teaching room. Other parameters like room geometry and seat placement have great influence in speech intelligibility. As an example, a lecture hall of 120 seats from Naval Academy „Mircea cel Batran“ is investigated using virtual simulations with ODEON software. The results of the simulations are discussed and some remarks are made regarding the current condition of the lecture hall.

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