R-weighting provides better estimation for rat hearing sensitivity

2000 ◽  
Vol 34 (2) ◽  
pp. 136-144 ◽  
Author(s):  
E. Böjrk ◽  
T. Nevalainen ◽  
M. Hakumäki ◽  
H.-M. Voipio
Keyword(s):  
Sound Pressure Level ◽  
Sound Pressure ◽  
Sound Level ◽  
Pressure Level ◽  
Sound Studies ◽  
Response Curves ◽  
Acoustic Environment ◽  
High Frequencies ◽  
Hearing Sensitivity ◽  
Sound Levels

Since sounds may induce physiological and behavioural changes in animals, it is necessary to assess and define the acoustic environment in laboratory animal facilities. Sound studies usually express sound levels as unweighted linear sound pressure levels. However, because a linear scale does not take account of hearing sensitivity-which may differ widely both between and within species at various frequencies-the results may be spurious. In this study a novel sound pressure level weighting for rats, R-weighting, was calculated according to a rat's hearing sensitivity. The sound level of a white noise signal was assessed using R-weighting, with H-weighting tailored for humans, A-weighting and linear sound pressure level combined with the response curves of two different loudspeakers. The sound signal resulted in different sound levels depending on the weighting and the type of loudspeaker. With a tweeter speaker reproducing sounds at high frequencies audible to a rat, R- and A-weightings gave similar results, but the H-weighted sound levels were lower. With a middle-range loudspeaker, unable to reproduce high frequencies, R-weighted sound showed the lowest sound levels. In conclusion, without a correct weighting system and proper equipment, the final sound level of an exposure stimulus can differ by several decibels from that intended. To achieve reliable and comparable results, standardization of sound experiments and assessment of the environment in animal facilities is a necessity. Hence, the use of appropriate species-specific sound pressure level weighting is essential. R-weighting for rats in sound studies is recommended.

Tutorial and Guidelines on Measurement of Sound Pressure Level in Voice and Speech

2018 ◽  
Vol 61 (3) ◽  
pp. 441-461 ◽  
Author(s):  
Jan G. Švec ◽  
Svante Granqvist
Keyword(s):  
Sound Pressure Level ◽  
Background Noise ◽  
Sound Pressure ◽  
Signal To Noise Ratio ◽  
Practical Experience ◽  
Sound Level ◽  
Pressure Level ◽  
Sound Levels ◽  
Frequency Weighting ◽  
Voice And Speech

Purpose Sound pressure level (SPL) measurement of voice and speech is often considered a trivial matter, but the measured levels are often reported incorrectly or incompletely, making them difficult to compare among various studies. This article aims at explaining the fundamental principles behind these measurements and providing guidelines to improve their accuracy and reproducibility. Method Basic information is put together from standards, technical, voice and speech literature, and practical experience of the authors and is explained for nontechnical readers. Results Variation of SPL with distance, sound level meters and their accuracy, frequency and time weightings, and background noise topics are reviewed. Several calibration procedures for SPL measurements are described for stand-mounted and head-mounted microphones. Conclusions SPL of voice and speech should be reported together with the mouth-to-microphone distance so that the levels can be related to vocal power. Sound level measurement settings (i.e., frequency weighting and time weighting/averaging) should always be specified. Classified sound level meters should be used to assure measurement accuracy. Head-mounted microphones placed at the proximity of the mouth improve signal-to-noise ratio and can be taken advantage of for voice SPL measurements when calibrated. Background noise levels should be reported besides the sound levels of voice and speech.

Mesa Verde National Park: Acoustic monitoring report

2021 ◽  
Author(s):  
Jacob Job
Keyword(s):  
Sound Pressure Level ◽  
National Park ◽  
Sound Pressure ◽  
Sound Level ◽  
Pressure Level ◽  
Logarithmic Scale ◽  
Noise Sources ◽  
Mesa Verde ◽  
Sound Levels ◽  
Human Ear

In 2015, the Natural Sounds and Night Skies Division (NSNSD) received a request to collect baseline acoustical data at Mesa Verde National Park (MEVE). Between July and August 2015, as well as February and March 2016, three acoustical monitoring systems were deployed throughout the park, however one site (MEVE002) stopped recording after a couple days during the summer due to wildlife interference. The goal of the study was to establish a baseline soundscape inventory of backcountry and frontcountry sites within the park. This inventory will be used to establish indicators and thresholds of soundscape quality that will support the park and NSNSD in developing a comprehensive approach to protecting the acoustic environment through soundscape management planning. Additionally, results of this study will help the park identify major sources of noise within the park, as well as provide a baseline understanding of the acoustical environment as a whole for use in potential future comparative studies. In this deployment, sound pressure level (SPL) was measured continuously every second by a calibrated sound level meter. Other equipment included an anemometer to collect wind speed and a digital audio recorder collecting continuous recordings to document sound sources. In this document, “sound pressure level” refers to broadband (12.5 Hz–20 kHz), A-weighted, 1-second time averaged sound level (LAeq, 1s), and hereafter referred to as “sound level.” Sound levels are measured on a logarithmic scale relative to the reference sound pressure for atmospheric sources, 20 μPa. The logarithmic scale is a useful way to express the wide range of sound pressures perceived by the human ear. Sound levels are reported in decibels (dB). A-weighting is applied to sound levels in order to account for the response of the human ear (Harris, 1998). To approximate human hearing sensitivity, A-weighting discounts sounds below 1 kHz and above 6 kHz. Trained technicians calculated time audible metrics after monitoring was complete. See Methods section for protocol details, equipment specifications, and metric calculations. Median existing (LA50) and natural ambient (LAnat) metrics are also reported for daytime (7:00–19:00) and nighttime (19:00–7:00). Prominent noise sources at the two backcountry sites (MEVE001 and MEVE002) included vehicles and aircraft, while building and vehicle predominated at the frontcountry site (MEVE003). Table 1 displays time audible values for each of these noise sources during the monitoring period, as well as ambient sound levels. In determining the current conditions of an acoustical environment, it is informative to examine how often sound levels exceed certain values. Table 2 reports the percent of time that measured levels at the three monitoring locations were above four key values.

Research of Possibilities of Using the Recycled Materials Based on Rubber and Textiles Combined with Vermiculite Material in the Area of ​​Noise Reduction

2014 ◽  
Vol 1001 ◽  
pp. 171-176 ◽  
Author(s):  
Pavol Liptai ◽  
Marek Moravec ◽  
Miroslav Badida
Keyword(s):  
Absorption Coefficient ◽  
Standing Wave ◽  
Sound Pressure Level ◽  
Sound Absorption ◽  
Sound Pressure ◽  
Sound Level ◽  
Pressure Level ◽  
Sound Absorption Coefficient ◽  
Physical Parameters ◽  
Materials Research

This paper describes possibilities in the use of recycled rubber granules and textile materials combined with vermiculite panel. The aim of the research is the application of materials that will be absorbing or reflecting sound energy. This objective is based on fundamental physical principles of materials research and acoustics. Method of measurement of sound absorption coefficient is based on the principle of standing wave in the impedance tube. With a sound level meter is measured maximum and minimum sound pressure level of standing wave. From the maximum and minimum sound pressure level of standing wave is calculated sound absorption coefficient αn, which can take values from 0 to 1. Determination of the sound absorption coefficient has been set in 1/3 octave band and in the frequency range from 50 Hz to 2000 Hz. In conclusion are proposed possibilities of application of these materials in terms of their mechanical and physical parameters.

scholarly journals Investigation of Noise Pollution Distribution in Different Parts of Yazd Textile Factories

2021 ◽  
Author(s):  
Mohammad Javad Zare Sakhvidi ◽  
Hamideh Bidel ◽  
Ahmad Ali Kheirandish
Keyword(s):  
Occupational Exposure ◽  
Sound Pressure Level ◽  
Textile Industry ◽  
Sound Pressure ◽  
Noise Pollution ◽  
Sound Level ◽  
Pressure Level ◽  
Cross Sectional ◽  
Sound Pressure Levels ◽  
Different Parts

 Background: Chronic occupational exposure to noise is an unavoidable reality in the country's textile industry and even other countries. The aim of this study was to compare the sound pressure level in different parts of the textile industry in Yazd and in different parts of the textile industry. Methods: This cross-sectional study was performed on 930 textile workers in Yazd. A questionnaire was used to obtain demographic information and how to use protective equipment. Then, to obtain the sound pressure level of each unit and device and to use the measurement principles, a calibrated sound level meter was used. Then the results were analyzed using SPSS Ver.29 software. Results: The participants in this study were 714 males and 216 females with a mean age of 35.27 and 33.63 years, respectively. Seven hundred fifty-six participants (81.29%) were exposed to sound pressure levels higher than 85 dB. Among the participants, only 18.39% of the people used a protective phone permanently. Except for factory E, with an average sound pressure level of 77.78 dB, the rest of the factories had an average sound pressure level higher than the occupational exposure limit. The sound measurement results of different devices show that the sound pressure levels above 90 dB are related to the parts of Dolatab, Ring, Kinetting (knitting), Chanel, Autoconer, Dolakni, Open End, MultiLakni, Tabandegi, Texture, and Poy. Conclusion: Based on the results of the present study, noise above 90 dB is considered as one of the main risk factors in most parts of the textile industry (spinning and weaving), which in the absence of engineering, managerial or individual controls on it causes hearing loss in becoming employees of this industry

scholarly journals Sound Levels Forecasting in an Acoustic Sensor Network Using a Deep Neural Network

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 903 ◽  
Author(s):  
Juan M. Navarro ◽  
Raquel Martínez-España ◽  
Andrés Bueno-Crespo ◽  
Ramón Martínez ◽  
José M. Cecilia
Keyword(s):  
Neural Network ◽  
Sensor Network ◽  
Sound Pressure Level ◽  
Deep Neural Network ◽  
Sound Pressure ◽  
Noise Pollution ◽  
Pressure Level ◽  
Acoustic Sensor ◽  
Short Term ◽  
Sound Levels

Wireless acoustic sensor networks are nowadays an essential tool for noise pollution monitoring and managing in cities. The increased computing capacity of the nodes that create the network is allowing the addition of processing algorithms and artificial intelligence that provide more information about the sound sources and environment, e.g., detect sound events or calculate loudness. Several models to predict sound pressure levels in cities are available, mainly road, railway and aerial traffic noise. However, these models are mostly based in auxiliary data, e.g., vehicles flow or street geometry, and predict equivalent levels for a temporal long-term. Therefore, forecasting of temporal short-term sound levels could be a helpful tool for urban planners and managers. In this work, a Long Short-Term Memory (LSTM) deep neural network technique is proposed to model temporal behavior of sound levels at a certain location, both sound pressure level and loudness level, in order to predict near-time future values. The proposed technique can be trained for and integrated in every node of a sensor network to provide novel functionalities, e.g., a method of early warning against noise pollution and of backup in case of node or network malfunction. To validate this approach, one-minute period equivalent sound levels, captured in a two-month measurement campaign by a node of a deployed network of acoustic sensors, have been used to train it and to obtain different forecasting models. Assessments of the developed LSTM models and Auto regressive integrated moving average models were performed to predict sound levels for several time periods, from 1 to 60 min. Comparison of the results show that the LSTM models outperform the statistics-based models. In general, the LSTM models achieve a prediction of values with a mean square error less than 4.3 dB for sound pressure level and less than 2 phons for loudness. Moreover, the goodness of fit of the LSTM models and the behavior pattern of the data in terms of prediction of sound levels are satisfactory.

Statistical Study of the Instantaneous Values of Traffic Noise Sound Pressure Level

2002 ◽  
Vol 33 (8) ◽  
pp. 16-24
Author(s):  
Jesús Alba Fernández ◽  
Marcelino Ferri García ◽  
Jaime Ramis Soriano ◽  
Juan Antonio Martínez Mora
Keyword(s):  
Sound Pressure Level ◽  
Sound Pressure ◽  
Road Traffic ◽  
Traffic Noise ◽  
Relevant Information ◽  
Sound Level ◽  
Pressure Level ◽  
Road Traffic Noise ◽  
Statistical Parameters ◽  
Sound Event

In environmental acoustics the knowledge of the time dependency of the sound level provides relevant information about a sound event. In this sense, it may be said that conventional sound level metres have frequently implemented programs to calculate the fractiles (percentiles) of the distribution of instantaneous sound levels; and there are several indexes to evaluate the noise pollution, based on different statistical parameters. For further analysis of sound, and to obtain the commented indexes, it is accepted that this distribution is normal or gaussian. The questions we've tried to solve in this work are the following: First of all, whether the time dependent distribution of the variable sound pressure level should be considered as Gaussian in general cases or only in some particular ones. On the other hand, we have studied how the frequency of the sampling affects the resulting distribution of a given a sound event. To these ends, a set of road traffic noise events has been evaluated. Furthermore, even in gaussian distributions of sound pressure levels, the average of the distribution will not be coincident with the equivalent sound pressure level; that is the level of the average quadratic pressure. The difference between this parameter, and its dependence on the standard deviation, is studied.

Average Is the New Loudest

2016 ◽  
Vol 26 ◽  
pp. 56-59
Author(s):  
Johannes Mulder
Keyword(s):  
Sound Pressure Level ◽  
Sound Pressure ◽  
Pressure Level ◽  
Audio Engineering ◽  
Sound Levels ◽  
Live Music ◽  
Measurement Strategies ◽  
Audio Production

This article discusses new sound pressure level (SPL) measurement strategies in the context of live music. A brief overview of the introduction of loudness normalization in broadcast audio engineering precedes a discussion of using average sound levels in measurements at concerts. The article closes with a short analysis of the implications of these developments for the notion of agency in the sociotechnical domain of audio production.

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