The dataset provides noise data to facilitate the tracking of trends in transportation-related noise. This dataset includes results from simplified noise modeling methods and should not be used to evaluate noise levels in individual locations. See the documentation for a full description of methodologies and assumptions: https://doi.org/10.21949/1519111 The 2018 National Transportation Noise Map dataset utilized transportation mode input data from 2018 in a model and is current as of October 2020, published by the Bureau of Transportation Statistics (BTS), and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). Please see the website https://www.bts.gov/geospatial/national-transportation-noise-map, for downloads and more information about these datasets. For web services of these data, please navigate to https://geo.dot.gov/server/rest/services/Hosted and search for service names beginning with "Noise." Data within the National Transportation Noise Map represent potential noise levels across the nation for an average annual day for the specified year. These data are intended to facilitate the tracking of trends in transportation-related noise by mode collectively over time and should not be used to evaluate noise levels in individual locations and/or at specific times. This dataset is developed using a 24-hr equivalent A-weighted sound level (denoted by LAeq) noise metric. The results represent the approximate average noise energy due to transportation noise sources over a 24-hour period at the receptor locations where noise is computed. Layers include Aviation, Passenger Rail (prototype), and Road Noise for the Lower 48 States as well as Alaska and Hawaii. The full listing can be found below. 2018 National Transportation Noise Alaska Alaska Aviation Noise Alaska Road and Aviation Noise Alaska Road Noise Lower 48 States (CONUS) Lower 48 States (CONUS) Aviation Noise Lower 48 States (CONUS) Passenger Rail Noise (prototype) Lower 48 States (CONUS) Passenger Rail, Road, and Aviation Noise (prototype) Lower 48 States (CONUS) Road and Aviation Noise Lower 48 States (CONUS) Road Noise Hawaii Hawaii Aviation Noise Hawaii Road and Aviation Noise Hawaii Road Noise

The 2020 National Transportation Noise Map dataset utilized transportation mode input data from 2020 in a model and is current as of October 2022, published by the Bureau of Transportation Statistics (BTS), and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). Please see the website https://www.bts.gov/geospatial/national-transportation-noise-map, for downloads and more information about these datasets. For web services of these data, please navigate to https://geo.dot.gov/server/rest/services/Hosted and search for service names beginning with "Noise." Please contact j.goworowska@dot.gov for any questions. Data within the National Transportation Noise Map represent potential noise levels across the nation for an average annual day for the specified year. These data are intended to facilitate the tracking of trends in transportation-related noise by mode collectively over time and should not be used to evaluate noise levels in individual locations and/or at specific times. This dataset is developed using a 24-hr equivalent A-weighted sound level (denoted by LAeq) noise metric. The results represent the approximate average noise energy due to transportation noise sources over a 24-hour period at the receptor locations where noise is computed. Layers include Aviation, Freight and Passenger Rail, and Road Noise for the Lower 48 States as well as Alaska and Hawaii. The full listing can be found below. 2020 National Transportation Noise

      Alaska

             Alaska Aviation Noise
             Alaska Freight and Passenger Rail Noise
             Alaska Freight and Passenger Rail, Road, and Aviation Noise
             Alaska Road and Aviation Noise
             Alaska Road Noise

      Lower 48 States (CONUS)

             Lower 48 States (CONUS) Aviation Noise
             Lower 48 States (CONUS) Freight and Passenger Rail Noise
             Lower 48 States (CONUS) Freight and Passenger Rail, Road, and Aviation Noise
             Lower 48 States (CONUS) Road and Aviation Noise
             Lower 48 States (CONUS) Road Noise

      Hawaii

             Hawaii Aviation Noise
             Hawaii Road and Aviation Noise
             Hawaii Road Noise

The 2016 National Transportation Noise Map dataset utilized transportation mode input data from 2016 in a model and is current as of October 2020, published by the Bureau of Transportation Statistics (BTS), and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). Please see the website https://www.bts.gov/geospatial/national-transportation-noise-map, for downloads and more information about these datasets. For web services of these data, please navigate to https://geo.dot.gov/server/rest/services/Hosted and search for service names beginning with "Noise." Please contact the NTAD Program Manager at ntad@dot.gov for any questions. Data within the National Transportation Noise Map represent potential noise levels across the nation for an average annual day for the specified year. These data are intended to facilitate the tracking of trends in transportation-related noise by mode collectively over time and should not be used to evaluate noise levels in individual locations and/or at specific times. This dataset is developed using a 24-hr equivalent A-weighted sound level (denoted by LAeq) noise metric. The results represent the approximate average noise energy due to transportation noise sources over a 24-hour period at the receptor locations where noise is computed. Layers include Aviation and Road Noise for the Lower 48 States as well as Alaska and Hawaii. The full listing can be found below. 2016 National Transportation Noise

      Alaska

             Alaska Aviation Noise
             Alaska Road and Aviation Noise
             Alaska Road Noise

      Lower 48 States (CONUS)

             Lower 48 States (CONUS) Aviation Noise
             Lower 48 States (CONUS) Road and Aviation Noise
             Lower 48 States (CONUS) Road Noise

      Hawaii

             Hawaii Aviation Noise
             Hawaii Road and Aviation Noise
             Hawaii Road Noise

In 2019, the majority of noise pollution was caused by service or commercial activities (61.4 percent), followed by production activities (26.1 percent). By contrast, airport infrastructures caused one percent of controlled noise pollution, whereas activities related to port infrastructures held 0.3 percent of the share.

This is a collection of data sets acquired for measurements of noise figure and receive system noise of wireless/radio frequency receivers and transceivers. These data include tabular data that list 1) Inputs: calibrated input signal and excess noise levels, and 2) Outputs: summary statistics for each type of user data collected for each DUT. The experiments that produced these data were meant to be used to assess noise measurands, but the data are generic and could be applied to other problems if desired. The structure of each zip archive dataset is as follows: | Root |-- (Anonymized DUT name 1) |---- Data file 1 |---- Data file 2 |---- ...Data file N |---- DUT-README.txt |-- (Anonymized DUT name 2) |---- Data file 1 |---- Data file 2 |---- ...Data file N |---- DUT-README.txt | (etc.) Data tables in each archive are provided as comma-separated values (.csv), and the descriptive text files are ASCII (.txt). Detailed discussion of the test conditions and data formatting is given by the DUT-README.txt for each DUT.

The 2018 National Transportation Noise Map dataset utilized transportation mode input data from 2018 in a model and is current as of October 2020, published by the Bureau of Transportation Statistics (BTS), and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). Please see the website https://www.bts.gov/geospatial/national-transportation-noise-map, for downloads and more information about these datasets. For web services of these data, please navigate to https://geo.dot.gov/server/rest/services/Hosted and search for service names beginning with "Noise." Please contact the NTAD Program Manager at ntad@dot.gov for any questions. Data within the National Transportation Noise Map represent potential noise levels across the nation for an average annual day for the specified year. These data are intended to facilitate the tracking of trends in transportation-related noise by mode collectively over time and should not be used to evaluate noise levels in individual locations and/or at specific times. This dataset is developed using a 24-hr equivalent A-weighted sound level (denoted by LAeq) noise metric. The results represent the approximate average noise energy due to transportation noise sources over a 24-hour period at the receptor locations where noise is computed. Layers include Aviation, Passenger Rail (prototype), and Road Noise for the Lower 48 States as well as Alaska and Hawaii. The full listing can be found below. 2018 National Transportation Noise

      Alaska

             Alaska Aviation Noise
             Alaska Road and Aviation Noise
             Alaska Road Noise

      Lower 48 States (CONUS)

             Lower 48 States (CONUS) Aviation Noise
             Lower 48 States (CONUS) Passenger Rail Noise (prototype)
             Lower 48 States (CONUS) Passenger Rail, Road, and Aviation Noise (prototype)
             Lower 48 States (CONUS) Road and Aviation Noise
             Lower 48 States (CONUS) Road Noise

      Hawaii

             Hawaii Aviation Noise
             Hawaii Road and Aviation Noise
             Hawaii Road Noise

Noise statistics for the main routes The Federal Railway Office is a result of the noise mapping – the noise statistics – not only in the map service, but also a summary of the data by federal state is available. In addition to this, the table contains information on the municipal noise index. The table shows, by federal state, the noise statistics and the noise index by municipality within the mapping scope along the main federal railway lines for the day-evening-night-noise index (LDEN) and night-noise index (LNIGHT) noise indices. The noise statistics provide information about the inhabitants polluted by noise, the polluted area and the estimated number of apartments, school and hospital buildings in the corresponding level classes. The noise index describes the noise situation in relation to the noise level and the inhabitants affected by it.

DEMAND: Diverse Environments Multichannel Acoustic Noise Database

A database of 16-channel environmental noise recordings

Introduction

Microphone arrays, a (typically regular) arrangement of several microphones, allow for a number of interesting signal processing techniques. The correlation of audio signals from microphones that are located in close proximity with each other can, for example, be used to determine the spatial location of sound source relative to the array, or to isolate or enhance a signal based on the direction from which the sound reaches the array.

Typically, experiments with microphone arrays that consider acoustic background noise use controlled environments or simulated environments. Such artificial setups will in general be sparse in terms of noise sources. Other pre-existing real-world noise databases (e.g. the AURORA-2 corpus, the CHiME background noise data, or the NOISEX-92 database) tend to provide only a very limited variety of environments and are limited to at most 2 channels.

The DEMAND (Diverse Environments Multichannel Acoustic Noise Database) presented here provides a set of recordings that allow testing of algorithms using real-world noise in a variety of settings. This version provides 15 recordings. All recordings are made with a 16-channel array, with the smallest distance between microphones being 5 cm and the largest being 21.8 cm.

License

This work, the audio data and the document describing it, is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License.

The data

A description of the data and the recording equipment is provided in the file DEMAND.pdf. All recordings are available as 16 single-channel WAV files in one directory at both 48 kHz and 16 kHz sampling rates. All files are compressed into "zip" files.

Other information

The MATLAB scripts listed in the documentation can be found in the file scripts.zip.

The Authors

This work was created by Joachim Thiemann (IRISA-CNRS), Nobutaka Ito (University of Tokyo), and Emmanuel Vincent (Inria Rennes - Bretagne Atlantique). It was supported by Inria under the Associate Team Program VERSAMUS.

Spatial Analysis of Urban Noise Pollution: We conducted a spatial analysis of the distribution of noise pollution across HOLC grades for 83 cities in the United States (data in HOLC_Noise_City_results.csv). To be included in the study, the city needed to be included in both datasets used in the analysis: 1) the Mapping Inequality Project dataset on the distribution of HOLC grades across cities, and 2) the U.S. Department of Transportation, National Transportation Noise Map 2018. Any cities in which the distribution of HOLC grades did not include all four grades (A-D) were excluded from the analysis, which largely excluded cities with population sizes below 100,000 people. To evaluate noise exposure across HOLC grades for each city in our study, we acquired spatial data on the distribution of HOLC grades across U.S. cities from the Mapping Inequality Project. We also acquired data on road, rail, and aircraft noise (hereafter transportation noise models), from the U.S. Department of Transportation, National Transportation Noise Map (2018). The transportation noise models represent potential exposure to transportation noise reported on a decibel scale in a 30m x 30m pixel resolution. Here noise represents the average noise energy produced by road, rail, and aviation networks over a 24-hour period, measured in A-weighted decibels (dBA) (LAeq, 24h) at sampling locations deployed across a uniform grid in each city at an elevation of 1.5 m above ground level. Noise levels below 35 dBA are assumed to have minimal negative impacts to humans and the environment and thus are represented with null values in the transportation noise models. For each HOLC grade and each city, we used zonal statistics in ArcGIS Desktop v. 10.7 to summarize the median noise levels and area covered by excess noise (i.e., values > 35 dBA). We used the resulting zonal statistics estimates and the formula from Collins et al. (2019) to calculate an area-corrected measure of excess noise:

N = (r * Md)/a

where N is excess noise in each HOLC grade (with units of dBA/900m2); r is the area covered by the 30m x 30m pixels with noise values >35 dBA across all polygons of the same HOLC grade in each city; Md is the median transportation noise value (in dBA) for those same pixels; and a is the total area of all polygons of the same HOLC grade in each city. Thus, N represents a measure of both the level of noise and the area covered by excess noise in a given HOLC grade for each city.

Literature Review on the Impacts of Noise to Urban Wildlife: To assess the effects of noise on wildlife in urban environments, we conducted a literature review using Thompson’s ISI Web of Science and adapting the methods of Shannon et al. (2016). We adjusted of Shannon et al.’s search criteria to include urban phrases, resulting in the following search terms (TS=(WILDLIFE OR ANIMAL OR MAMMAL OR REPTILE OR AMPHIBIAN OR BIRD OR FISH OR INVERTEBRATE) AND TS=(NOISE OR SONAR) AND TS=(CITY OR *URBAN OR METROPOLITAN)). We only selected papers published between 1990 and 23 June 2021 (i.e., the date we conducted our search) within the ISI Web of Science categories of ‘Acoustics’, ‘Zoology’, ‘Ecology’, ‘Environmental Sciences’, ‘Ornithology’, ‘Biodiversity Conservation’, ‘Evolutionary Biology’, and ‘Marine Freshwater Biology’. This returned 691 peer-reviewed papers, which we filtered so only empirical studies focused on documenting the effects of anthropogenic noise on wildlife in urban or suburban ecosystems or the effects of urban noise on wildlife in rural environments were included in the final data set (n = 207). We excluded reviews, meta-analyses, methods papers, and research that took place outside of urban or suburban areas where the noise was not explicitly denoted as urban (e.g., omitted studies that measured traffic noise by parks and reserves in rural areas). For the 241 articles previously analyzed in of Shannon et al. (2016), one of our authors reviewed each paper to determine which studies were focused on urban noise (n = 46). We then verified whether there were significant biological responses to a particular noise level threshold, noting each noise level if multiple biological responses were recorded. We recorded responses to noise into one of eight possible biological response categories, many of which were taken or modified from the biological response categories utilized in Shannon et al. (2016). The following were the biological response categorical values: movement behavior, vocal behavior, physiological, population, mating behavior, foraging behavior, vigilance behavior, life history / reproduction, and ecosystem. For any new articles published since the Shannon et al. (2016) dataset (n = 354) or those published between 1990 and 2013 but not reviewed by Shannon et al. (n = 96), two of our authors reviewed each paper to first determine which studies met our criteria (n = 161) and then compiled data on a number of variables of interest, including the noise levels and their resulting biological responses that were statistically significant. For this subset of papers, one author was randomly assigned a list of papers and then a second author was randomly assigned to assess the accuracy of the data collected by the first author. Any discrepancies were discussed as a group until an agreement was reached. Noise categories (environmental, transportation, industrial, multiple, other) were chosen for each paper by noting the explicitly stated source or description of urban noise described in the methodology. Noise levels and their units were reported for each paper, with only noise levels reported in decibels (dB) being used in data analysis. All terrestrial papers used a reference pressure of 20 microPascals (μPa). Due to the low sample size of aquatic studies (n = 4), differences in reference pressures, and varying sound intensities amongst aquatic studies, we only included terrestrial studies in statistical analyses and figures. We recorded the sound metric used (i.e., SPL, SPL Max, Leq) for each paper, but were unable to convert the various sound metrics given to a single sound metric for standardization during analysis. Thus, there were various sound metrics used in the analysis of the data extracted from the literature search, in particular for the cumulative weight-of-evidence curve, which poses a limitation in the comparison of noise levels amongst papers. Additionally, we recorded the weightings for each noise level, with many of the papers being A-weighted (dBA; n = 100) and Z-weighted (dBZ; n = 4). These weightings relate to typical characteristics of sounds as observed by humans. Many papers, however, did not record the weighting and/or the exact sound metric used.

The FSDnoisy18k dataset is an open dataset containing 42.5 hours of audio across 20 sound event classes, including a small amount of manually-labeled data and a larger quantity of real-world noisy data. The audio content is taken from Freesound, and the dataset was curated using the Freesound Annotator. The noisy set of FSDnoisy18k consists of 15,813 audio clips (38.8h), and the test set consists of 947 audio clips (1.4h) with correct labels. The dataset features two main types of label noise: in-vocabulary (IV) and out-of-vocabulary (OOV). IV applies when, given an observed label that is incorrect or incomplete, the true or missing label is part of the target class set. Analogously, OOV means that the true or missing label is not covered by those 20 classes.

In 2023, the roadside areas in Bangkok Metropolitan Region in Thailand recorded an average 24-hour noise level (Leq) of 69.6 dB(A), indicating a slight increase compared to the previous year. The areas with the average noise level exceeding the standard range were Phahurat Road, Tri Phet Road, and Din Daeng Road.

Data indicating the level of noise according to the strategic noise mapping of road sources within areas with a population of at least 100,000 people (agglomerations) and along major traffic routes. Lden indicates a 24 hour annual average noise level with separate weightings for the evening and night periods. Noise levels are modeled on a 10m grid at a receptor height of 4m above ground, polygons are then produced by merging neighboring cells within the following noise classes: 75.0+ dB, 70.0-74.9 dB, 65.0-69.9 dB, 60.0-64.9 dB, 55.0-59.9 dB, <54.9 dB This data is a product of the strategic noise mapping analysis undertaken in 2017 to meet the requirements of the Environmental Noise Directive (Directive 2002/49/EC) and the Environmental Noise (England) Regulations 2006 (as amended).

Data indicating the level of noise according to the strategic noise mapping of rail sources across England.

• The day-evening-night level (Lden) is a noise indicator for overall annoyance based upon annual average A-weighted long-term sound over 24 hours with a 5 dB(A) penalty for evening noise (19:00-23:00) and a 10 dB(A) penalty for night-time noise (23:00-07:00).
• The 16-hour equivalent continuous level (LAeq,16h) is a noise indicator which describes the annual average steady noise level over the 16-hour daytime period (07:00 to 23:00) which contains the same sound energy as the actual fluctuating sound across the same period.
• The day level (Lday) is a daytime noise indicator based upon annual average A-weighted long-term sound over the daytime period (07:00-19:00) which contains the same sound energy as the actual fluctuating sound across the same period.
• The evening level (Leve) is an evening noise indicator based upon annual average A-weighted long-term sound over the evening period (19:00-23:00) which contains the same sound energy as the actual fluctuating sound across the same period.
• The night level (Lnight) is a night-time noise indicator based upon annual average A-weighted long-term sound over the night period (23:00-07:00) which contains the same sound energy as the actual fluctuating sound across the same period.
• The 6-hour equivalent continuous level (LAeq,6h) is a noise indicator which describes the annual average steady noise level over the 6-hour period (24:00 to 06:00) which contains the same sound energy as the actual fluctuating sound across the same period.
• The 18-hour equivalent continuous level (LAeq,18h) is a noise indicator which describes the annual average steady noise level over the 18-hour period (06:00 to 24:00) which contains the same sound energy as the actual fluctuating sound across the same period.

Noise levels are modelled on a 10m grid at a receptor height of 4m above ground, with a lower threshold cutoff of 35dB for the Lnight and LAeq,6h metrics, and 40dB for all other metrics. Data is available for all railway sources and also those defined as "major" under the Regulations.

This data is a product of the strategic noise mapping analysis undertaken in 2022 to meet the requirements of the Environmental Noise (England) Regulations 2006 (as amended).

Data indicating the level of noise according to the strategic noise mapping of road sources within areas with a population of at least 100,000 people (agglomerations) and along major traffic routes. Lnight indicates night time annual average noise level results in dB, where night is defined as 2300 - 0700. Noise levels are modeled on a 10m grid at a receptor height of 4m above ground, polygons are then produced by merging neighboring cells within the following noise classes: 70.0+ dB, 65.0-69.9 dB, 60.0-64.9 dB, 55.0-59.9 dB, 50-54.9 dB, <49.9 dB This data is a product of the strategic noise mapping analysis undertaken in 2017 to meet the requirements of the Environmental Noise Directive (Directive 2002/49/EC) and the Environmental Noise (England) Regulations 2006 (as amended).

Data indicating the level of noise according to the strategic noise mapping of road sources within areas with a population of at least 100,000 people (agglomerations) and along major traffic routes. LAeq,16h indicates the annual average noise levels for the 16-hour period between 0700 – 2300. Noise levels are modeled on a 10m grid at a receptor height of 4m above ground, polygons are then produced by merging neighboring cells within the following noise classes: 75.0+dB, 70.0-74.9dB, 65.0-69.9dB, 60.0-64.9dB, 55.0-59.9dB, <54.9dB. This data is a product of the strategic noise mapping analysis undertaken in 2017 to meet the requirements of the Environmental Noise Directive (Directive 2002/49/EC) and the Environmental Noise (England) Regulations 2006 (as amended)

The dataset contains workplace noise measurement results collected during health hazards evaluation surveys from 1997 to 2013 for over 800 personal noise exposure assessments. The collected data about exposure are based on OSHA and NIOSH assessment criteria and are accompanied by description of location, industry, work type, working area, the activity that generates exposure, use of specific personal protective equipment as well as other variables.

Strategic noise maps (DF 4 and DF 8) related data as listed in annex VI of Directive 2002/49/EC for major roads, railways, airports and agglomerations • Per agglomeration ≥ 100,000 inhabitants • For overall major roads ≥ 3 millions vehicles per year • For overall major railways ≥ 30,000 trains per year • For major airports ≥ 50,000 air traffic movements per year

Dataset Card for instruction-background-noise-data-synthetic

This dataset has been created with distilabel.

  Dataset Summary

This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI: distilabel pipeline run --config "https://huggingface.co/datasets/jan-hq/instruction-background-noise-data-synthetic/raw/main/pipeline.yaml"

or explore the configuration: distilabel pipeline info… See the full description on the dataset page: https://huggingface.co/datasets/Menlo/instruction-background-noise-data-synthetic.

250Hz

Areas which the Secretary of State considers to be urban (with a population greater than or equal to 100,000 people) where, under the Environmental Noise Directive (Round 2), Defra is required to undertake Strategic Noise Mapping.