Find research datasets worth reusing

opencc-zeroJan 2021View details →

Data from: The allometry of sound frequency bandwidth in songbirds

Theory predicts that allometric constraints on sound production should be stronger for the lower frequencies of vocalizations than for their higher frequencies, which could originate an allometry for sound frequency bandwidth, but this was never tested. Using song recordings of ca. 1000 passerine species (from >75% passerine genera), we show a significantly steeper allometry for the lower than the higher song frequencies, resulting in a positive allometry of frequency bandwidth: larger species can use wider bandwidths than smaller species. The bandwidth allometry exists in songbirds (oscines), but not non-oscine passerines, indicating that it emerges from a combination of physical constraint and the evolved behavior of oscines: unlike the narrow bandwidths of most non-oscine songs, the learned songs of oscines often use wide bandwidths that can be limited by both the lower and upper limits of sound frequency production. This bandwidth allometry has implications for several research topics in acoustic communication.

opencc-zeroFeb 2021View details →

Chum salmon escapement on Bonanza River in Norton Sound, Alaska

Bonanza River flows 40 rkm south from the Kigluaik Mountains and drains into Safety Sound approximately 39 km northeast of Nome, Alaska. Chum, pink, and coho salmon are the predominant species that return to the Bonanza River. A fixed-picket weir was installed approximately 11 rkm above the Bonanza Bridge on the Nome-Council Highway (GPS coordinates 64°32.964ʹN, 164°35.812ʹW). The Bonanza River weir enumerated chum salmon for three seasons from 2018 to 2020. Chum salmon escapements were 7,903 in 2018; 8,824 in 2019; and 2,471 in 2020. In 2018 and 2019, high water delayed installation of the weir and therefore the beginning of the run may have been missed. Additionally, in 2019 high water forced weir operations to stop before the proposed end date, so it is likely the end of the chum salmon run was missed. In 2020, the weir went in according to schedule and counted the beginning of the run, but personnel issues, exacerbated by COVID-19 protocols, resulted in early termination of the project, and likely caused missed counting at the end of the run. High water that hindered counting on Bonanza River in 2018 and 2019 also hindered counting operations on other Subdistrict 1 rivers, and as a result aspects of Objectives 1 and 2 could not be completed for all project years. Age, sex, and length data were collected from chum salmon passing through the weir in all three years. Minimum sample size requirements to evaluate Objective 3 were met in 2018 and 2020, but not in 2019. In 2018, chum salmon were predominantly 4 years old and in 2020 chum salmon were predominantly 5 years old. This project indicated that using existing methods, such as weirs and aerial surveys, to estimate Bonanza River's contribution to chum salmon abundance in Subdistrict 1 provide a reasonable approximation of chum salmon escapement in the absence of an enumeration project on Bonanza River.

opencc-zeroJul 2019View details →

Data from: Flowers respond to pollinator sound within minutes by increasing nectar sugar concentration.

Can plants sense natural airborne sounds and respond to them rapidly? We show that Oenothera drummondii flowers, exposed to playback sound of a flying bee or to synthetic sound-signals at similar frequencies, produce sweeter nectar within 3 minutes, potentially increasing the chances of cross pollination. We found that the flowers vibrated mechanically in response to these sounds, suggesting a plausible mechanism where the flower serves as an auditory sensory organ. Both the vibration and the nectar response were frequency-specific: the flowers responded and vibrated to pollinator sounds, but not to higher frequency sound. Our results document for the first time that plants can rapidly respond to pollinator sounds in an ecologically relevant way. Potential implications include plant resource allocation, the evolution of flower shape, and the evolution of pollinators sound. Finally, our results suggest that plants may be affected by other sounds as well, including antropogenic ones.

opencc-by-4.0Jan 2024View details →

Fig 1 from: Kuga T, Kasuya E (2024) Factors related to sound production by the Chinese grasshopper Acrida cinerea during escape. Journal of Orthoptera Research 33(1): 13-19. https://doi.org/10.3897/jor.33.100865

Fig 1 Photos of male A. cinerea (A) and its habitat where field experiments were conducted (B).

openother-ncApr 2019View details →

TAU Moving Sound Events 2019 - Ambisonic, Reverberant, Real-life IR and Moving Source Dataset

Tampere University (TAU) Moving Sound Events 2019 - Ambisonic, Reverberant and Real-life Impulse Response and Moving Source Dataset This dataset consists of real-life first order Ambisonic (FOA) format recordings with moving point sources each in 2D spherical space represented with azimuth and elevation angles. The dataset was generated by collecting impulse responses (IR) from a real environment using the Eigenmike spherical microphone array. The measurement was done by slowly moving a Genelec G Two loudspeaker continuously playing a maximum length sequence around the array in circular trajectory in one elevation at a time. The playback volume was set to be 30 dB greater than the ambient sound level. The recording was done in a corridor inside the university with classrooms around it during work hours. The IRs were collected at elevations −40 to 40 with 10-degree increments at 1 m from the Eigenmike and at elevations −20 to 20 with 10-degree increments at 2 m.  The dataset consists of three sub-datasets with a) maximum one temporally overlapping sound events, b) maximum two temporally overlapping sound events, and c) maximum three temporally overlapping sound events. Each of the sub-datasets has three cross-validation splits, that consists of 240 recordings of about 30 seconds long for training split and 60 recordings of the same length for the testing split. All sound events in this dataset are moving only along azimuth with a constant angular velocity in the range [-90, 90]/s with 10-degree/s steps. For each recording, the metadata file with the same name consists of the sound event name, the temporal onset and offset time (in seconds), starting spatial location in azimuth and elevation angles (in degrees), the angular velocity of motion and distance from the microphone (in meters). The isolated sound events were taken from the urbansound8k dataset. This dataset consists of 10 sound event classes such as air_conditioner, car_horn, children_playing, dog_bark, drilling, enginge_idling, gun_shot, jackhammer, siren, and street_music. We do not consider air_conditioner and children_playing sound events. Further, we only include the sound event examples marked as foreground in the dataset. We used the splits 1, 8 and 9 provided in the urbansound8k as the three CV splits. These splits were chosen as they had a good number of examples for all the chosen sound event classes after selecting only the foreground examples. During the sound scene synthesis, every sound event is assigned a spatial trajectory on an arc with a constant distance from the microphone and moving with a constant angular velocity for its duration. Other than the license file, there are nine zip files that consist of the dataset and corresponding metadata for given split and overlap. For example, the ov3_split1.zip file consists of training and testing recordings and metadata for the case of a maximum of three temporally overlapping sound events (ov3) for the first cross-validation split (split1). Within each folder, the filenames for training split have the 'train' prefix, while the testing split filenames have the 'test' prefix. This dataset was collected as part of the '<a href="https://github.com/sharathadavanne/seld-net">Localization, Detection and Tracking of Multiple Moving Sound Sources with Convolutional Recurrent Neural Networks'</a> work. Data collector (s): Fagerlund, Eemi; Koskimies, Aino; Hakala, Aapo

opencc-by-4.0Oct 2019View details →

The effect of spatial energy spread on sound image size and speech intelligibility [dataset]

This dataset contains the data and supplementary material for the publication titled "The effect of spatial energy spread on sound image size and speech intelligibility" published in the Journal of the Acoustical Society of America. This repository contains the results from the three experiments as well as a figure showing the adaptive tracks of the adaptive procedure and the estimated psychometric functions in experiment 3. The subject identifiers are common across the three experiments. Experiment 1: Factors: Subject/Listener, ambisonics order, audio/stimulus type, spatial location of stimulus, room condition, repetition Measured variables: Source image size, source direction (azimuth), source distance Experiment 2: Factors: Subject/Listener, ambisonics order, interferer location, room condition Measured variable: Speech reception threshold (SRT) Experiment 3: Factors: Subject/Listener, ambisonics order, repetition Measured variable: Speech reception angle (SRA) The figure (exp3_adaptiveTracks.png) shows the adaptive tracks in experiment 3. Each panel shows one of the ambisonics orders. The x-axis is the trial number and the y-axis the separation angle between target and interfering talkers. Each color indicates one subject. The figure (exp3_psychometricFcns.png) shows the estimated psychometric functions in experiment 3. Each panel shows one of the ambisonics orders. The x-axis is the separation angle between target and interfering talkers and the y-axis is the percent correct words. Each color indicates one subject. The black line indicates the median over the subjects and repetitions and the black cross the SRA predicted with this method.

restrictedcc-by-nc-4.0Sep 2024View details →

ARTSOUNDSCAPES PROJECT - REPOSITORY OF ANECHOIC SOUNDS

This dataset was organised by members of the Artsoundscapes project. It serves as a library of anechoic music and sounds created by the Artsoundscapes project. It includes musical pieces of a great variety of genres and styles to nourish the different research lines. The Venezuelan musician and instrument maker, Yonder Rodriguez, played diverse membranophones and several reconstructions of archaeological instruments, such as Palaeolithic bone pipes, whistles and bullroarers, diverse kinds of rattles and scrapers, and traditional and shamanic Amazonian instruments. Catalan traditional music and other foreign traditions, such as Altaian traditional music, were performed by Guillem Codern, a Catalan musician who is well versed in traditional Tuvan music, such as khoomei and other vocal styles. Aditionally, singers María Illa (female voice) and Julen Gerrikabeitia (male voice), performed a selection of contemporary the pop-rock pieces. More detail about the sound excerpts selected for the stimulus set is provided in the ARTSS-Anechoic recording list (excel file). Data collection was organized by Samantha López-Mochales and Raquel Jiménez-Pasalodos, assisted by Lidia Alvarez-Morales and Margarita Díaz-Andreu. All the sounds were recorded in uncompressed mono format in the anechoic chamber at the La Salle Acoustics Laboratory (Ramon Llull University, Barcelona, Spain) in July 2021. Dr Marc Arnela, Carme Julia Martínez Suquia and Raquel Aparicio-Terres helped during the recording sessions. For the intellectual rights and the distribution policy of the audio recordings in this dataset contact Dr Margarita Díaz-Andreu. If you use our dataset, please email us at <a href="mailto:artsoundscapesproject@gmail.com">artsoundscapesproject@gmail.com</a> and tell us about your research.

openOct 2024View details →

THE INFLUENCE OF SOCIAL PROMOTION ON SOUND CHANGES

The work which is provided in the following pages concerns the explicit observation of sound variations and alterations in the context of real community lives which stems from considering social factors by synthesizing case studies to conclude.

opencc-by-4.0Oct 2024View details →

Gunshot sound files and spectrogram images from passive acoustic monitoring data in Vietnam.

<h3>Introduction</h3> This dataset was created to support benchmarking of automated gunshot detection models using 'torch for R'. The data includes recordings collected from Chu Mom Ray National Park in Vietnam combined with an open dataset of gunshots from Belize (Katsis et al. 2022). The dataset is organized into several folders containing .jpg images and their corresponding .wav audio clips.  <h3>Data Summary</h3> The dataset is divided into three main categories based on the region and use case: <ol> <li>imagesvietnamunbalanced: Contains spectrogram images and audio data collected from Chu Mom Ray National Park in Vietnam. These data are used for training and evaluating automated gunshot detection models.</li> <li>imagesvietnam_belize: Includes spectrogram images and audio data from both Vietnam and Belize. The data in this folder is used for benchmarking model performance across different geographical regions.</li> <li>testdatacombined: Separate test data to evaluate performance with a large number of noise clips, representing real-world automated detection scenarios.</li> </ol> Each .jpg image in these directories is associated with a .wav file representing a corresponding audio clip. The .wav files were recorded using passive acoustic monitoring and clips were isolated using manual annotations in Raven Pro Software. If used please cite:  Vu, T. T., Phan, D. V., Le, T. S., & Clink, D. J. (2024). Investigating hunting in a protected area in Southeast Asia using passive acoustic monitoring with mobile smartphones and deep learning. Ecological Indicators.  Vu, T. T., Phan, D. V., Le, T. S., & Clink, D. J. (2024). Gunshot sound files and images from passive acoustic monitoring data in Vietnam. [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.13893977" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.13893977</a> Katsis, Lydia; Hill, Andrew; Piña-Covarrubias, Evelyn; Prince, Peter; Rogers, Alex; Doncaster, C. Patrick; Snaddon, Jake (2022), “Tropical forest gunshot classification training audio dataset”, Mendeley Data, V3, doi: 10.17632/x48cwz364j.3

openNov 2024View details →

Sound field image with objects dataset

<h2>Description</h2> This sound field image with objects dataset contains clean-noisy pairs of complex-valued sound-field images generated by 2D acoustic simulations. The dataset was initially prepared for SoundSil-DS (https://github.com/nttcslab/soundsil-ds), a DNN-based denoising method for optically measured sound fields. Please check our GitHub repository and paper for details. <h2> Directory structure</h2> The dataset contains three directories: training, validation, and evaluation. Each directory contains "soundsource#" sub-directories (# represents the number of sound sources used in the acoustic simulation). Each sub-directory has three h5 files for data (clean, white noise, and object-mask) and one CSV file listing random parameter values used in the simulation. - /training     - /soundsource#        - sf_true.h5        - sf_noise_white.h5        - mask_data.h5        - random_variables.csv

opencc-zeroDec 2017View details →

Data from: Would an RRS by any other name sound as RAD?

1. Sampling markers throughout a genome with restriction enzymes emerged in the 2000s as reduced representation shotgun sequencing (RRS). Rapid advances in sequencing technology have since spurred modifications of RRS, giving rise to many derivatives with unique names, such as restriction site-associated DNA sequencing (RADseq). But naming conventions have often been more creative than consistent and criteria for recognizing unique methods have been unclear, resulting in a proliferation of names characterized by ambiguity. 2. We give an overview of methodological and etymological relationships among 36 restriction enzyme-based methods, and survey the consistency of references to five prominent methods in the literature. 3. We identified several instances of methodological convergence, and note that many published derivatives have modified only minor elements of parent protocols. Misattribution through ambiguous or inconsistent literature references was observed in 8.4% of journal articles citing the original one and two-enzyme RADseq and GBS, as well as SBG publications. 4. The rapid expansion of names associated with derivative protocols is confusing and, in many cases, unwarranted. We urge greater restraint in naming derivative methods and suggest general guidelines for naming that promote a balance between clarity, descriptiveness, and recognition of scientific innovation.

opencc-zeroDec 2015View details →

Data from: Statistical analysis for subjective and objective evaluations of dental drill sounds

The sound produced by a dental air turbine handpiece (dental drill) can markedly influence the sound environment in a dental clinic. Indeed, many patients report that the sound of a dental drill elicits an unpleasant feeling. Although several manufacturers have attempted to reduce the sound pressure levels produced by dental drills during idling based on ISO 14457, the sound emitted by such drills under active drilling conditions may negatively influence the dental clinic sound environment. The physical metrics related to the unpleasant impressions associated with dental drill sounds have not been determined. In the present study, psychological measurements of dental drill sounds were conducted with the aim of facilitating improvement of the sound environment at dental clinics. Specifically, we examined the impressions elicited by the sounds of 12 types of dental drills in idling and drilling conditions using a semantic differential. The analysis revealed that the impressions of dental drill sounds varied considerably between idling and drilling conditions and among the examined drills. This finding suggests that measuring the sound of a dental drill in idling conditions alone may be insufficient for evaluating the effects of the sound. We related the results of the psychological evaluations to those of measurements of the physical metrics of equivalent continuous A-weighted sound pressure levels (LAeq) and sharpness. Factor analysis indicated that impressions of the dental drill sounds consisted of two factors: "metallic and unpleasant" and "powerful". LAeq had a strong relationship with "powerful impression", calculated sharpness was positively related to "metallic impression", and "unpleasant impression" was predicted by the combination of both LAeq and calculated sharpness. The present analyses indicate that, in addition to a reduction in sound pressure level, refining the frequency components of dental drill sounds is important for creating a comfortable sound environment in dental clinics.

opencc-by-4.0Nov 2022View details →

Convolutional Neural Networks for Scops Owl Sound Classification

These are the training, validation, and testing datasets used in a publication titled "Convolutional Neural Networks for Scops Owl Sound Classification" . Each set consists of WAV files of seven Indonesian scops owl species. If you use this dataset for your research publication please cite the following paper: <a href="https://doi.org/10.1016/j.procs.2020.12.010">https://doi.org/10.1016/j.procs.2020.12.010</a>

opencc-by-4.0Dec 2019View details →

Intense cicada – Quesada Gigas – ambience from Catamarca8 in Collecting Sounds. Online Sharing of Field Recordings as Cultural Practice

Intense cicada – Quesada Gigas – ambience from Catamarca8

opencc-byMar 2021View details →

Hardwick Sounding House, Whitchurch on Thames.

This model is comprised of 52 photos and is a rudimentary model of the site to plot the positions of 4 test pits, excavated by local resident archaeologists, Nick, Rory and Sarah, and instigated by local SOAG member Simon Smith. This site is located in the woods behind Hardwick House and is colloquialy known as The Bear Pit. It is likely the crater was the result a chalk/flint quarry, which also served as a lime kiln or an ice house, serving Hardwick House. Later augmented to become a Victorian folly, as a destination for recreational walks and theatrical performances. Excavated on 28th March 2021 as a preliminary evaluation of the archaeological potential of the site, and to assess the state of disrepair and decay since the excavations by SOAG in 1970, 1974 and 1987. Source: Objaverse 1.0 / Sketchfab

opencc-by-nc-4.0Mar 2017View details →

Single Sound Spectral Clarity Dataset

Data generated as part of the PhD research of Kirsten Hermes [1], to determine how the impact of spectral equalisation (EQ) on the perceived clarity of sound can be predicted.  Data comprise audio files, listening test interfaces, results, and MATLAB code for modelling and for plot generation.   References 1. K.Hermes, "Towards measuring music mix quality: the factors contributing to the spectral clarity of single sounds", PhD Thesis, IoSR, University of Surrey, UK, 2017

restrictedIPD-UNDECIDEDFeb 2026View details →

Lymphedema Therapy With Sound Wave Lymphatic Drainage

ClinicalTrials.gov study NCT01115374. IPD Sharing: Not stated. Countries: 1. Publications: 0.

controlledIPD-YESFeb 2026View details →

Wearable Electronic Breath Sound Sensing Device

ClinicalTrials.gov study NCT06734793. IPD Sharing: YES. Countries: 1. Publications: 0.

closedIPD-NOFeb 2026View details →

AutoFocus360 Sound Quality Preference and Claims Study

ClinicalTrials.gov study NCT07224919. IPD Sharing: NO. Countries: 0. Publications: 0.