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1,719 results for “songs”
CoHERE Work Package 3 Survey of Inhabitants of Baltic Countries on Song and Dance Celebrations
<p>Part of Work Package 3 for the 'Critical Heritages' research project ( https://research.ncl.ac.uk/cohere/researchstrands/#WP3%20Cultural%20forms%20and%20expressions%20of%20identity%20in%20Europe ).</p> <p>One of the key case studies in CoHERE Work Package 3 has been the Song and Dance Celebration tradition in the Baltic states (included in the UNESCO list as a masterpiece of the oral and intangible heritage of humanity in 2003). The case study reveals several aspects of this festival: cultural, economic, social dimensions and governance. Through examining different aspects of this festival tradition and everyday practices it responds to several objectives of the WP3. Being a key social and cultural event in three Baltic countries, it provides a ground for debates on how performative practices and festivals can contribute to identity construction and transformation, developing sense of belonging, serve as platform for where heritage practices of different social groups can meet.</p>
Exploring Vocatives in Folk Songs of the Podillia Region
<p>This dataset is based on the folklore collection <em>Pisni Podillia: zapysy Nasti Prysiazhniuk v seli Pohrebyshche. 1920-1970 rr.</em> (Myshanych 1976). The collection consists of 850 songs, encompassing 13,005 lines and 78,888 tokens. Vocatives were manually distinguished and recorded in a separate column in the corpus without the assistance of RStudio, due to the complexity of distinguishing vocatives in Ukrainian.</p> <p>Vocatives in Ukrainian folk songs were analysed using the R programming language along with RStudio. </p> <p>Code written for text analysis in Estonian Literary Museum. </p> <p> </p> <p>This dataset consists of the following files:</p> <p>1. <strong>vocatives_Podillia_folk_songs.R</strong>: R script used for analyzing the corpus, including vocative counting, song length analysis, POS-tag analysis, semantic group and structural types analysis. </p> <p>2. <strong>corpus_vocatives.csv</strong>: Contains the text data of Podillia folk songs with manually distinguished vocatives. </p> <p>3. <strong>corpus_POS_tokens.csv</strong>: Contains verified the POS-tagged tokens of the corpus.</p> <p> </p>
Ovenbird song recordings from Alberta (Canada) with individual labels and spatial locations, 2015-2016
This dataset includes spatially localized and individually identified Ovenbird songs. We used automated species detection and acoustic localization to localize Ovenbird singing events from microphone arrays in Alberta, Canada (2015-2016). We then hand-annotated songs to individuals based on acoustic characteristics. This dataset includes the manual annotations and annotations from automated individual identification approaches. This data publication pertains to the manuscript [in prep] by Lapp et al on Ovenbird individual identification and provides further details on the study and the individual identification approach.
Song Describer Dataset
<h2>The Song Describer Dataset: a Corpus of Audio Captions for Music-and-Language Evaluation</h2><blockquote><p><i>A retro-futurist drum machine groove drenched in bubbly synthetic sound effects and a hint of an acid bassline.</i></p></blockquote><p>The Song Describer Dataset (SDD) contains ~1.1k captions for 706 permissively licensed music recordings. It is designed for use in evaluation of models that address music-and-language (M&L) tasks such as music captioning, text-to-music generation and music-language retrieval. More information about the data, collection method and validation is provided in the paper describing the dataset.</p><p>If you use this dataset, please cite <a href="https://arxiv.org/abs/2311.10057">our paper</a>:</p><p>The Song Describer Dataset: a Corpus of Audio Captions for Music-and-Language Evaluation, Manco, Ilaria and Weck, Benno and Doh, Seungheon and Won, Minz and Zhang, Yixiao and Bogdanov, Dmitry and Wu, Yusong and Chen, Ke and Tovstogan, Philip and Benetos, Emmanouil and Quinton, Elio and Fazekas, György and Nam, Juhan, Machine Learning for Audio Workshop at NeurIPS 2023, 2023</p>
Song et al., 2022_iScience_DATASET
<p>This dataset contains the underlying data (energy sector data for India) for the book chapter Song et al., 2022 published in Science in May 2022.</p>
An acoustically isolated European starling song library
<p>A dataset of song collected from 14 European starlings individually recorded in acoustically isolated chambers. Each folder contains vocalizations for one bird.</p> <p>These data were used for the publication, "<em>Parallels in the sequential organization of birdsong and human speech</em>". Nature Communications (2019). If you use this dataset, please cite this publication and this repository.</p> <p>Work supported by NSF Graduate Research Fellowship 2017216247 to TS and an NIH R56DC016408 to TQG.</p>
UCSB SONGS Mitigation Monitoring: Reef Performance Standard - Benthic Algae and Macroinvertebrate Cover, Abundance, and Richness
These data describe annual estimates of the percent cover, abundance, and species richness (evaluated as species density) of benthic macroalgae and macroinvertebrates from replicate transects at three subtidal reefs. Data collection began in 2009 at an artificial reef (Wheeler North Reef in Orange County, CA) and two natural reference reefs (San Mateo Kelp in Orange County, CA and Barn Kelp in San Diego County, CA) to evaluate the ability of Wheeler North Reef to compensate for losses of kelp forest habitat and associated biota caused by the operation of the San Onofre Nuclear Generating Station (SONGS).
UCSB SONGS Mitigation Monitoring: Wetland Performance Standard - Fish Abundance and Species Richness
These data describe the annual estimates of density of wetland fish (all species combined) and the species richness (as the number of unique species) in six main channel and six tidal creek locations at four coastal wetlands as part of the SONGS San Dieguito Wetland Restoration monitoring program to track long-term patterns in species abundance and diversity. This study began in 2012 in the San Dieguito Wetland in San Diego County, CA, Carpinteria Salt Marsh in Santa Barbara County, CA, and Mugu Lagoon in Ventura County, CA. Tijuana Estuary in San Diego County was added in 2013. Beginning in 2024, Tijuana Estuary was replaced with Los Penasquitos Lagoon in San Diego County, CA.
UCSB SONGS Mitigation Monitoring: Wetland Performance Standard - Bird Abundance and Species Richness
These data describe the annual estimates of bird density and richness (as a species density) in twenty plots at four coastal wetlands as part of the SONGS San Dieguito Wetland Restoration monitoring program to track long-term patterns in species abundance and diversity. This study began in 2012 in the San Dieguito Wetlands and Tijuana Estuary in San Diego County, CA, Carpinteria Salt Marsh in Santa Barbara County, CA, and Mugu Lagoon in Ventura County, CA. Beginning in 2024, Tijuana Estuary was replaced with Los Penasquitos Lagoon in San Diego County, CA.
UCSB SONGS Mitigation Monitoring: Wetland Performance Standard - Bird Food Chain Support
These data describe annual estimates of the density of feeding birds at four coastal wetlands as part of the SONGS San Dieguito Wetland Restoration monitoring program to track long-term patterns in food chain support provided to birds. This study began in 2012 in the San Dieguito Wetlands and Tijuana Estuary in San Diego County, CA, Carpinteria Salt Marsh in Santa Barbara County, CA, and Point Mugu Lagoon in Ventura County. Beginning in 2024, Tijuana Estuary was replaced with Los Penasquitos Lagoon in San Diego County, CA.
UCSB SONGS Mitigation Monitoring: Wetland Performance Standard - Invertebrate Abundance and Richness
These data contain annual estimates of the density of wetland macroinvertebrates (all species combined) and species richness (as a species density) in six main channel and six tidal creek locations at four coastal wetlands as part of the SONGS San Dieguito Wetland Restoration monitoring program to track long-term patterns in species abundance and diversity. This study began in 2012 in the San Dieguito Wetland and Tijuana Estuary in San Diego County, CA, Carpinteria Salt Marsh in Santa Barbara County, CA, and Mugu Lagoon in Ventura County, CA. Beginning in 2024, Tijuana Estuary was replaced with Los Penasquitos Lagoon in San Diego County, CA.
UCSB SONGS Mitigation Monitoring: Wetland Performance Standard - Spartina Canopy
These data describe annual estimates of Spartina foliosa canopy architecture (measured as proportion of stems > 3 ft long) from four locations at two coastal wetlands as part of the SONGS San Dieguito Wetland Restoration mitigation monitoring program to track long-term patterns in Spartina size structure. This study began in 2012 in the San Dieguito Wetlands and Tijuana Estuary in San Diego County, CA. Beginning in 2024, Tijuana Estuary was replaced with Mugu Lagoon in Ventura County, CA.
UCSB SONGS Mitigation Monitoring: Wetland Performance Standard - Water Quality
These data describe annual estimates of wetland water quality, measured as the average duration of hypoxia (time dissolved oxygen concentration below 3 mg/l), collected as part of the SONGS San Dieguito Wetland Restoration mitigation monitoring program designed to evaluate compliance of the restoration project with conditions of the SONGS permit. This study began in 2012 in the San Dieguito Wetlands and Tijuana Estuary in San Diego County, CA, Carpinteria Salt Marsh in Santa Barbara County, CA, and Point Mugu Lagoon in Ventura County, CA. Beginning in 2024, Tijuana Estuary was replaced with Los Penasquitos Lagoon in San Diego County, CA.
UCSB SONGS Mitigation Monitoring: Wetland Performance Standard - Tidal Prism
These data describe estimates of tidal prism at the San Dieguito Wetland as part of the SONGS San Dieguito Wetland Restoration mitigation monitoring program to track long-term patterns of tidal prism. This study began in 2012.
UCSB SONGS Mitigation Monitoring: Wetland Performance Standard - Plant Reproductive Success
These data describe annual estimates reproductive success (measured by seed set) of salt marsh plants at the San Dieguito Wetland as part of the SONGS San Dieguito Wetland Restoration mitigation monitoring program designed to track long-term patterns in reproductive success of wetland plants. Monitoring began in 2012.
UCSB SONGS Mitigation Monitoring: Reef Performance Standard - Kelp Acres
These data describe annual estimates of the area (in acres) of medium-to-high density adult giant kelp, Macrocystis pyrifera, supported by the artificial reef polygons of Wheeler North Reef in Orange County, CA (33.40210N, 117.62420W). Data collection began in 2009 to evaluate the ability of Wheeler North Reef to compensate for losses of kelp forest habitat and associated biota caused by the operation of the San Onofre Nuclear Generating Station (SONGS).
UCSB SONGS Mitigation Monitoring: Reef Performance Standard - Fish Standing Stock
These data describe annual estimates of fish standing stock (in tons) supported by the artificial reef, Wheeler North Reef, in Orange County, CA (33.40210N, 117.62420W). Data collection began in 2009 to evaluate the ability of Wheeler North Reef to compensate for losses of kelp forest habitat and associated biota caused by the operation of the San Onofre Nuclear Generating Station (SONGS).
UCSB SONGS Mitigation Monitoring: Reef Performance Standard - Fish Abundance and Richness
These data describe annual estimates of the density and species richness (evaluated as species density) of young-of-year (less than 1 year old) and resident (greater than 1 year old) reef fish from replicate transects at three subtidal reefs. Data collection began in 2009 at an artificial reef (Wheeler North Reef in Orange County, CA) and two natural reference reefs (San Mateo Kelp in Orange County, CA and Barn Kelp in San Diego County, CA) to evaluate the ability of Wheeler North Reef to compensate for losses of kelp forest habitat and associated biota caused by the operation of San Onofre Nuclear Generating Station (SONGS).
Duhumbi Religious Texts and Song - Transcribed, parsed, glossed, translated text files
<p>This data set contains the .wav sound files, .trs Transcriber files, .txt Toolbox-compatible Notepad files and .pdf files with the completely transcribed, glossed, parsed and translated examples of the following recordings that belong to the following publication:</p> <p>Bodt, Timotheus Adrianus. 2020. Grammar of Duhumbi. Leiden: Brill. ISBN 978-90-04-40947-7. <a href="https://brill.com/view/title/55767">https://brill.com/view/title/55767</a></p> <ul> <li>[CHUK110413A2A] / RELJ / Buddhist admonition</li> <li> [CHUK221212D2A] / JIK / Bonpo prediction text</li> <li> [CHUK260413A1] / MSK / Impromptu song</li> </ul> <p>The explanation of all the grammatical features that occur in these sound files can be found in the Grammar of Duhumbi.</p> <p>The main Toolbox files can be found in the zip file “Settings”, this includes the IPA keys for Duhumbi, the entire setup of the Toolbox database, and the Duhumbi dictionary and Parsing dictionary.</p> <p>The .wav, .txt and .trs files combined in the same folder will enable to open Toolbox and work with the recordings, e.g. play them sentence for sentence and see the transcriptions and translations.</p> <p>Transcriber version 1.5.1: <a href="http://trans.sourceforge.net/en/presentation.php">http://trans.sourceforge.net/en/presentation.php</a> or <a href="https://osdn.net/projects/sfnet_trans/downloads/transcriber/1.5.1/Transcriber-1.5.1-Windows.exe/">https://osdn.net/projects/sfnet_trans/downloads/transcriber/1.5.1/Transcriber-1.5.1-Windows.exe/</a></p> <p>Toolbox version 1.6.1: <a href="https://software.sil.org/toolbox/download/">https://software.sil.org/toolbox/download/</a></p> <p>For the metadata of the sound files in this data set, I refer to Chapter 13 Texts in the Grammar of Duhumbi. This Chapter has a complete listing of the texts, their topics, the speakers and their background etc.</p> <p>This material is made freely available to everyone for informative or scientific purposes as long as the source (this DOI) / the collectors are properly credited. Please note that use of the material for commercial purposes <strong><em>of any kind</em></strong><em>, which includes conversion into commercial audio-visual media (documentaries etc.), storage and dissemination through sites that require registration & payment for access, or sites that rely on advertisement (including YouTube) </em>is <strong>not</strong> permitted without <strong>specific written consent</strong> from the speakers and their community, obtained through the collectors of the material. By downloading our material, you agree to these restrictions.</p> <p>This data set falls under the Attribution-NonCommercial-ShareAlike (CC BY-NC-SA) license. This license lets you remix, tweak, and build upon this work non-commercially, as long as you credit us and license your new creations under the identical terms. License Deed on <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/">https://creativecommons.org/licenses/by-nc-sa/4.0/</a>. Legal Code on <a href="https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode">https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode</a>.</p> <p>Tim Bodt: monpasang (at) gmail (dot) com</p>
Supplementary material for "Song et al., Modelling Simul. Mater. Sci. Eng., 2021: Data-mining of dislocation microstructures: concepts for coarse-graining of internal energies"
<p>This zip archive contains supplementary material in the form of datasets and jupyter notebooks that are used in the following publication:</p> <ul> <li>authors: Hengxu Song, Nina Gunkelmann, Giacomo Po, and Stefan Sandfeld</li> <li>journal: Modelling Simul. Mater. Sci. Eng.</li> <li>year: 2021</li> <li>title: Data-mining of dislocation microstructures: concepts for coarse-graining of internal energies</li> </ul>
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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)
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DANDI Archive for NWB datasets
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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.