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20 results for “classical music”
Cadenza Challenge (CAD2): databases for rebalancing classical music task
<h1>Cadenza</h1> <p>Please, cite CadenzaWoodwind as</p> <blockquote> <p><strong>Gerardo Roa-Dabike , Trevor J. Cox , Alex J. Miller , Bruno M. Fazenda , Simone Graetzer , Rebecca R. Vos , Michael A. Akeroyd , Jennifer Firth , William M. Whitmer , Scott Bannister , Alinka Greasley , Jon P. Barker , The Cadenza Woodwind Dataset: Synthesised Quartets for Music Information Retrieval and Machine Learning, Data in Brief (2024), doi: https://doi.org/10.1016/j.dib.2024.111199</strong></p> </blockquote> <p>This is the training and validation data for the rebalancing classic music task from the <a href="https://cadenzachallenge.org/">Second Cadenza Machine Learning Challenge (CAD2).</a></p> <p>The Cadenza Challenges are improving music production and processing for people with a hearing loss. According to The World Health Organization, 430 million people worldwide have a disabling hearing loss. Hearing aid users report several issues when listening to music, including distortion in the bass, difficulties in perceiving the full range of the music, especially high-frequency pitches, and a tendency to miss the impact of quieter parts of compositions [1]. In a pilot study, we found giving listeners sliders to allow them to rebalance different instruments in a classical music ensemble was desirable.</p> <p>Overview of files:</p> <ol> <li>CadenzaWoodwind. Synthesized dataset of small ensembles of woodwind instruments for training and validation.</li> <li>EnsembleSet_Mix_1. A subset of the synthesised <a href="../records/6519024">EnsembleSet [7]</a> for training and validation (Mix_1 render).</li> <li>Real Data for Tuning: <a href="../api/records/12664932/draft/files/Stereo_Reverb_Real_Data_For_Tuning.zip/content" target="_blank" rel="noopener noreferrer">Stereo_Reverb_Real_Data_For_Tuning.zip</a>.</li> <li>metadata.zip contains audiograms, scene details, target gains and compressor settings.</li> </ol> <p>The audio files are in FLAC format in the .zip archives. The json files contain metadata.</p> <p>More details below.</p> <p> </p>
Indian Semi-Classical Music Dataset
<p>This dataset is a collection of mel-spectrogram features extracted from Indian semi-classical music containing the following 9 semi-classical styles:<br> Bhajan, Chaiti, Dadra, Ghazal, Kajri, Natya Sangeet, Qawwali, Tappa, Thumri.</p> <p>The number of recordings varies from 25 (for Chaiti) to 50 in the mentioned styles representing the scarcity of availability of given folk styles on the Internet. There are at least 5 artists and a maximum of 13. Overall there are 48 artists (36 female + 12 male) in these 9 semi-classical styles. <br> There is a total of 425 recordings in the dataset, with a total duration of 54.69 hrs.<br> Mel-spectrogram is extracted from a 3-second segment with each song's 1/2 second sliding window. Extracted mel-spectrogram for each segment is annotated with the genre, artist, gender, song, source, no_of_artists, genre_id, artist_id, gender_id.<br> _________________________________________________________________________________________________________<br> This project was funded under the grant number: ECR/2018/000204 by the Science & Engineering Research Board (SERB).</p>
Hindustani Classical Music Transcription Dataset
<p>This dataset includes the transcriptions of Hindustani classical music recordings. Overall there are 430 pieces each having a 25-sec duration. These pieces include 329 Alap, 79 mid, and 22 end sections taken from 50 music recordings. Each transcription consists of annotations for Shrutis (22 in one octave) in 3 Shaptak (22 * 3 = 66), Alankar, and Silence or noise. We also include a symbol table mapping each annotation to a unique Unicode character.</p> <p> </p> <p>_________________________________________________________________________________________________________<br> This project was funded under grant number: ECR/2018/000204 by the Science & Engineering Research Board (SERB).</p>
Landmine Detection Using Electromagnetic Time Reversal-Based Methods. Part 1: Classical TR, Iterative TR, DORT and TR-MUSIC
<p>In this repository, you can find the simulation files used to reproduce the results presented in the paper titled "Landmine Detection Using Electromagnetic Time Reversal-Based Methods." If you find these files useful, please cite the paper as it helps acknowledge the work and support future research.</p> <p>This repository is organized into three main folders, each serving a distinct purpose and containing specific types of files:</p> <p><strong>CST-MWS Files</strong>: This folder contains the necessary files to simulate the examples discussed in the paper using CST Microwave Studio (CST-MWS). These files are essential for setting up and running the simulations that replicate the experimental results. </p> <p><strong>TR-MUSIC</strong>: In this folder, you will find the MATLAB m-file required to implement the TR-MUSIC (Time Reversal-MUltiple SIgnal Classification) method proposed in the paper. This MATLAB script is designed to help users apply the TR-MUSIC algorithm to their data, enabling them to detect landmines effectively. </p> <p><strong>2D-GFB</strong>: The 2D-GFB folder contains the MATLAB m-file necessary to run the 2D TR-MUSIC and DORT (Decomposition of the Time Reversal Operator) methods. These advanced techniques are crucial for analyzing two-dimensional data and enhancing the accuracy of landmine detection. </p> <p><br>By organizing the repository in this manner, we aim to make it easier for researchers and practitioners to access and utilize the simulation files effectively. Whether you are replicating the study's results or applying these methods to new datasets, the files and instructions provided should serve as a valuable resource.</p> <p>If you encounter any issues or have questions regarding the use of these files, please do not hesitate to reach out for support. We hope this repository aids your research and contributes to advancements in landmine detection technologies.</p> <p> </p>
Field Report on 3D Audio Capture of Solo Piano for Classical Music Productions - Audio Files
<p>This online repository contains audio files related to research on the side surround loudspeakers on 3D audio recordings of solo piano in classical music productions, undertaken by Emre Ekici, Will Howie, and Toru Kamekawa at Tokyo University of the Arts, March 2023. Please find the guidelines for usage below: </p> <p>The archive (3DPIANO_TRACKS.zip) contains 23 channels of mono audio tracks for ITU 4+7+0 solo piano recording, played by Yamaha Disklavier. Files are recorded at 96 kHz / 24-bit.</p> <p>File naming convention:<br> ##_ProjectTitle_Loudspeaker_Position/Variable_Position/Variable_Option (if applicable).</p> <p>Anyone is free to download and listen to these files for reference.</p> <p>If you wish to use these files for your research, please contact Emre Ekici (mrekici@outlook.com) or Will Howie (wghowie@gmail.com) for permission.</p>
Temporal relationship between dancer’s body movements and music beats in classical ballet
Open the record for dataset details and reuse information.
Ptolemy's adaptation of the Helikōn, diagram from Lynch, T.A.C. (forthcoming), 'Music', Oxford Classical Dictionary online.
<p>Ptolemy’s adaptation of the <em>Helikōn, </em>diagram from Lynch, T.A.C. (forthcoming), ‘Music’, Oxford Classical Dictionary online.</p>
Data from: Creating a multi-track classical music performance dataset for multi-modal music analysis: challenges, insights, and applications
We introduce a dataset for facilitating audio-visual analysis of musical performances. The dataset comprises 44 simple multi-instrument classical music pieces assembled from coordinated but separately recorded performances of individual tracks. For each piece, we provide the musical score in MIDI format, the audio recordings of the individual tracks, the audio and video recording of the assembled mixture, and ground- truth annotation files including frame-level and note-level tran- scriptions. We describe our methodology for the creation of the dataset, particularly highlighting our approaches for addressing the challenges involved in maintaining synchronization and ex- pressiveness. We demonstrate the high quality of synchronization achieved with our proposed approach by comparing the dataset against existing widely-used music audio datasets. We anticipate that the dataset will be useful for the devel- opment and evaluation of existing music information retrieval (MIR) tasks, as well as for novel multi-modal tasks. We bench- mark two existing MIR tasks (multi-pitch analysis and score- informed source separation) on the dataset and compare against other existing music audio datasets. Additionally, we consider two novel multi-modal MIR tasks (visually informed multi-pitch analysis and polyphonic vibrato analysis) enabled by the dataset and provide evaluation measures and baseline systems for future comparisons (from our recent work). Finally, we propose several emerging research directions that the dataset enables.
The Effect of Classical Music on Dental Students' Stress and Anxiety During the COVID-19 Pandemic
ClinicalTrials.gov study NCT06787833. IPD Sharing: YES. Countries: 1. Publications: 1.
Lullaby and Classic Music's Effect on Vital Findings and Comfort
ClinicalTrials.gov study NCT05333575. IPD Sharing: NO. Countries: 1. Publications: 7.
Live Classical Music and the Response to the Disease and Its Evolution in Patients With Chronic Renal Failure
ClinicalTrials.gov study NCT05729997. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Effect of Quranic Recitation and Classical Music on Pain Intensity and Interleukin-6 Levels After Lower Limb Orthopedic Surgery with Intrathecal Anesthesia
ClinicalTrials.gov study NCT06713044. IPD Sharing: NO. Countries: 1. Publications: 0.
Classical Turkish Music for Pregnant Women With Preeclampsia
ClinicalTrials.gov study NCT06315985. IPD Sharing: NO. Countries: 1. Publications: 11.
Data from: Creating a multi-track classical music performance dataset for multi-modal music analysis: challenges, insights, and applications
Open the record for dataset details and reuse information.
Recordings of classical music (voice with piano, piano solo) with smartphones and professional audio equipment
<p>To investigate differences of performance rating and perception of classical music demo videos, two demos were recorded with six devices (four Smartphones with main cam video function, one field recorder, one professional setup). Video and Audio were separated for each file, only the audio files were used in the study and are thus presented here. The music of the voice demo is from the genres of romantic lied and romantic and modern opera, the piano solo music was composed in the 20th century.</p> <p>The documentation follows the recommendations of the German Society for Acoustics (DEGA), the information is as following:</p> <p>A 3D model of the recording situation.<br>The audio files, normalised (as used in the corresponding study) and with original level.<br>Geometric measurements of room dimensions.<br>Pictures of the recording.<br>A list of the equipment and recording system.<br>Render statistics (provided by the DAW used, Reaper).<br>Scores of two of the three pieces.<br>A Takelist.</p>
Investigating CNN-Based Instrument Family Recognition for Western Classical Music Recordings
<p>This repository contains the data used for experiment 2 (both patch- and file-based) to reproduce the results from the ISMIR paper.</p> <p>If you wish to know more about the dataset and experiment 1, please contact us.</p>
The Relation Between Midwifery Education and Listening to Classical Music With the Mode of Delivery
ClinicalTrials.gov study NCT04104009. IPD Sharing: NO. Countries: 1. Publications: 0.
A Study to Evaluate the Impact of Classical Music on Perceived Waiting Time and Satisfaction in Emergency Department Patients
ClinicalTrials.gov study NCT06973993. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Therapeutic Melodies: How Classical Turkish Music Soothes Stress and Eases Loneliness
ClinicalTrials.gov study NCT05859893. IPD Sharing: YES. Countries: 1. Publications: 0.
The Effect of Classical and Harp Music Practice on Premature Infants
ClinicalTrials.gov study NCT05647005. IPD Sharing: YES. Countries: 1. Publications: 0.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.