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opencc-by-4.0May 2021View details →

Labeled songs of domestic canary M1-2016-spring (Serinus canaria)

Labeled songs of domestic canary M1-2016-spring (Serinus canaria) J. Giraudon*123, N. Trouvain*123, A. Cazala4, C. Del Negro4, X. Hinaut123 1 Inria Bordeaux Sud-Ouest, France 2 LaBRI, Bordeaux INP, CNRS, UMR 5800, France 3 Institut des Maladies Neurogégénératives, Université de Bordeaux, CNRS, UMR 5293, France 4 Paris-Saclay University, UMR 9197 CNRS, Paris-Saclay Institute of Neuroscience, France  * these authors participated equally to this work. General information This dataset contains ~3h of labeled songs (459 songs) of one male canary (called M1) recorded between May 24th and June 15th 2016. Songs were recorded in a sound-isolation chamber using a RODE M3 microphone, an external sound card for microphone amplification (M-Audio Fast Track Ultra 8R), and the software Sound Analysis Pro 2011 (SAP). SAP parameters were set with conservative thresholds (software threshold to 4-6) in order to record the initiation of canary's songs which can be low in volume. Songs were hand labelled by one human expert using Audacity. They were then checked and corrected by another human expert assisted by an automated program based on recurrent neural networks (see References). Dataset description Canary songs are labeled using 27 different identified syllable classes + 1 "call" class identifying simple off-song calls + 1 "TRASH" class for irrelevant sounds (very rare vocalizations or non-bird sounds) + 1 "SIL" class for silence between vocalizations. Songs are annotated at the phrase level: a phrase consists of a repetition of a single syllable type and each phrase type is assigned a label. Annotations are provided in CSV format in the "M1-2016-spring_csv_annotations.zip" archive. There is one file per song, containing: <ul> <li>a "wave" column indicating the song's audio filename;</li> <li>"start" and "end" columns indicating the temporal delimitation of the label from the begining of the song, in seconds;</li> <li>a "syll" column indicating the labels.</li> </ul> Annotations are also provided in <a href="https://manual.audacityteam.org/man/importing_and_exporting_labels.html">Audacity TXT format</a> in the "M1-2016-spring_audacity_annotations.zip" archive. There is one file per song, containing three tabulation-separated columns. The first two column indicates the temporal delimitation (start and end) of the phrase from the begining of the song. The thrid one contains the associated label. Annotations filenames match corresponding song audio filename. Songs are provided in WAV format (44kHz sampling rate) in the "M1-2016-spring_audio.zip" archive. There is one file per song: audio filenames match corresponding annotation filenames. References This dataset was used in: N. Trouvain, X. Hinaut (2021) Canary Song Decoder: Transduction and Implicit Segmentation with ESNs and LTSMs. HAL preprint <a href="https://hal.inria.fr/hal-03203374">&lang;hal-03203374&rang;</a>

opencc-by-4.0Jun 2022View details →

Bag of pitch classes for Japanese enka songs

This dataset is comprised of 827 songs, curated from the following publications: (a) Y. Goto (ed.), Grand Collection of Enka Songs by Female Singers 5th Ed. (in Japanese), Zen-on Music Co., 2016. (b) Y. Goto (ed.), Grand Collection of Enka Songs by Male Singers 5th Ed. (in Japanese), Zen-on Music Co., 2016. Upon the use of this work, we kindly ask to explicitly cite/mention this paper, where the dataset was first used: [1] Eita Nakamura, Kentaro Shibata, Ryo Nishikimi, Kazuyoshi Yoshii, “Unsupervised melody style conversion,” Proc. 44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 196-200, May 2019. ** Data ** EnkaDataBagOfPitchClasses.tsv Each line represents a song. The first column indicates the song's location in the publications. For example, EnkaF-030_p027 indicates the 30th song on page 27 by a female artist in (a). From the second column to the 13th column, the numbers represent the counts for pitch classes from C to B. Tied notes were merged and counted only once.

opencc-by-4.0Aug 2018View details →

Duhumbi Religious Texts and Song - Sound files

This data set contains all the original sound files of the religious texts and the song in the 'Grammar of Duhumbi' (Brill) published in 2019. A separate Zenodo DOI contains all the Toolbox-compatible .txt files and Transcriber .trs files with the transcribed, parsed, glossed, translated examples (DOI 10.5281/zenodo.1406181). The following list contains the sound file names, the shortcut code for the sentence names and the title of the text. <ul> <li>[CHUK110413A2A] / RELJ / Buddhist admonition</li> <li> [CHUK221212D2A] / JIK / Bonpo prediction text</li> <li> [CHUK260413A1] / MSK / Impromptu song</li> </ul> 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 of any kind, 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) is not permitted without specific written consent from the speakers and their community, obtained through the collectors of the material. By downloading our material, you agree to these restrictions. 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>. Tim Bodt: bodttim (at) gmail (dot) com

opencc-by-4.0Nov 2023View details →

D-PLACE dataset derived from Bertolo et al. 2023 'Cross-cultural music corpus: The Expanded Natural History of Song Discography'

Cite the source of the dataset as: <blockquote> Mila Bertolo, Martynas Snarskis, Manvir Singh, & Samuel Mehr. (2023, August 8). Cross-cultural music corpus: The Expanded Natural History of Song Discography. Zenodo. https://doi.org/10.5281/zenodo.8378337 </blockquote>

opencc-by-sa-4.0Nov 2024View details →

Song capturing lived-experiences of flooding and climate resilience with St. Eugenes Choir Newtownstewart (BluePrint project)

This audio piece represents one of the creative risk communication outputs co-created within the BluePrint project. Between March and October 2024, socially engaged artist Sara Walmsley worked creatively with flood-affected community representatives in Newtownstewart, Co. Tyrone and Eglinton, Co. Derry-Londonderry exploring their lived-experiences of flooding and need for climate adaptation and resilience.  In the audio piece, you will hear the melodic, polyphonic harmonies of St. Eugene’s Church choir (Newtownstewart) as they give music to the words of members of their community whose homes were destroyed and lives endangered by flood water. The piece captures the voices of those striving to adapt to our changing climate, those who are responding to the urgency by finding solace, hope, strength and courage in the unending and unsurprising resilience and creativity of our communities.  The BluePrint project is led by the MaREI Centre, University College Cork, with partners the Playhouse, Derry City and Strabane District Council, and Mayo County Council. The BluePrint project is a recipient of the Creative Climate Action fund, an initiative from the Creative Ireland Programme. It is funded by the Department of Tourism, Culture, Arts, Gaeltacht, Sport and Media in collaboration with the Department of the Environment, Climate and Communications.  Find out more: <a href="https://www.marei.ie/project/blueprint/">https://www.marei.ie/project/blueprint/</a>

opencc-by-4.0May 2022View details →

Song Interpretation Dataset

The Song Interpretation Dataset combines data from two sources: (1) music and metadata from the Music4All Dataset and (2) lyrics and user interpretations from SongMeanings.com. We design a music metadata-based matching algorithm that aligns matching items in the two datasets with each other. In the end, we successfully match 25.47% of the tracks in the Music4All Dataset. The dataset contains audio excerpts from 27,834 songs (30 seconds each, recorded at 44.1 kHz), the corresponding music metadata, about 490,000 user interpretations of the lyric text, and the number of votes given for each of these user interpretations. The average length of the interpretations is 97 words. Music in the dataset covers various genres, of which the top 5 are: Rock (11,626), Pop (6,071), Metal (2,516), Electronic (2,213) and Folk (1,760).  For more details, please refer to our paper "Interpreting Song Lyrics with an Audio-Informed Pre-trained Language Model".

opencc-by-4.0Feb 2023View details →

SHS-YouTube1300: A YouTube-based Cover Song Dataset (Crema-PCP Features)

These are the CREMA-PCP Features for our SHS-YouTube-1300 dataset and crawl. This crawl is based on the SHS100K dataset and contains YouTube videos of which a subset was annotated by crowd-workers and in-house annotators.

opencc-by-4.0Sep 2022View details →

Occasional songs from the Royal Shooting Association in Copenhagen, Denmark (1782–1869)

The data set is centered around a catalogue (enumerative bibliography) of occasional songs addressed to an illustrious recipient at parties organized by the Royal Copenhagen Shooting Association (Det Kongelige Kjøbenhavnske Skydeselskab og Danske Broderskab). A more detailed description will be found in the research article with the title "Increasing Access to Ephemeral Prints. How to Construct and Analyze a Dataset From the Golden Age of Literature in Nineteenth-Century Denmark" (submitted to the journal Orbis Litterarum, in August 2022). The dataset was also published as a printed Danish bibliography entitled Holger Berg: Kongesange og skydeviser fra Det Kongelige Kjøbenhavnske Skydeselskab og Danske Broderskab 1784-1869. Odense: Kle-Art, 2022. ISBN 978-87-92750-35-8

openCC (other)Mar 2024View details →

SONGS Mitigation Monitoring: Experimental Reef Survey - Giant Kelp Outplant Size-Specific Survivorship

These data describe the size-specific survivorship of laboratory-reared embryonic giant kelp, Macrocystis pyrifera, outplanted at an artificial reef (Wheeler North Reef in Orange County, CA). In summer 2000 divers deployed an average of 56 outplant units containing embryonic kelp to 14 modules of Wheeler North Reef. Size specific survivorship was measured by recording the number and size of outplanted kelp on surviving outplant units three and eleven months after deployment. Measurements of size were categorical and included small single blades (recruits), multi-bladed plants less than 1m tall, and multi-frond plants equal or greater than 1 m tall.

UCSB SONGS Mitigation Monitoring: Reef Performance Standard – Fish Production

These data describe annual estimates of the somatic and gonadal tissue production in five species of reef fishes 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). Data were collected from 2009 – 2023 as part of a comprehensive mitigation program aimed at evaluating 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).

openCC (other)Aug 2025View details →

UCSB SONGS Mitigation Monitoring: Wetland Survey - Fish Abundance

These data describe annual estimates of the density of fish in main channel and tidal creek habitats 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. Monitoring 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, Los Penasquitos Lagoon in San Diego County replaced Tijuana Estuary. The abundance of fish is determined using beach seine and enclosure trap sampling at six main channel and six tidal creek locations at each wetland. Both seine and enclosure trap sampling consist of several hauls through an enclosed volume of water. Sampling is conducted annually in early fall.

UCSB SONGS Mitigation Monitoring: Wetland Survey - Bird Abundance

These data describe annual estimates of bird density 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. Monitoring 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. Los Penasquitos Lagood in San Diego County replaced Tijuana Estuary in 2024. The abundance of birds is determined from twenty plots spread across each wetland.

UCSB SONGS Mitigation Monitoring: Wetland Survey - Bird Feeding Activity

These data describe annual estimates of shorebird bird feeding activity, measured as the percentage of birds observed feeding, 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. Monitoring 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. Bird feeding activity was estimated for twenty plots in each wetland having at least one targeted shorebird species present on the ground. Beginning in 2024, Tijuana Estuary was replaced with Los Penasquitos Lagoon in San Diego County, CA.

openCC (other)Aug 2025View details →

UCSB SONGS Mitigation Monitoring: Wetland Survey - Invertebrate Abundance

These data describe the abundance of invertebrate species sampled in quadrats and sediment cores as part of the SONGS San Dieguito Wetland Restoration monitoring program to track long-term patterns in species abundance and diversity and assess compliance of the restoration project with conditions in the SONGS Coastal Development permit. This study began in 2012 in the San Dieguito Lagoon and Tijuana Estuary in San Diego County, CA, Carpinteria Salt Marsh in Santa Barbara County, CA, and Mugu Lagoon in Ventura County, CA. The abundance of invertebrates in quadrats and sediment cores was recorded at six main channel and six tidal creek locations at each wetland. Beginning in 2024, Tijuana Estuary was replaced with Los Penasquitos Lagoon in San Diego County, CA.

UCSB SONGS Mitigation Monitoring: Wetland Survey - Spartina Size Structure

These data describe annual estimates of Spartina foliosa size structure 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. Monitoring began in 2012 in the San Dieguito Wetlands and Tijuana Estuary in San Diego County, CA. The height of Spartina stems were recorded along four transects at each wetland. Beginning in 2024, Tijuana Estuary was replaced with Mugu Lagoon in Ventura County, CA.

UCSB SONGS Mitigation Monitoring: Wetland Survey - Water Quality

These data describe measurements of water characteristics (temperature, salinity, and dissolved oxygen) 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. Monitoring 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. Measurements of water depth, temperature, salinity, and dissolved oxygen were recorded daily in fifteen minute intervals at two sampling stations (primary and backup) at the San Dieguito Wetland, Carpinteria Salt Marsh, and Mugu Lagoon, and one sampling station (primary) at the Tijuana Estuary (2012-2023) and Los Penasquitos Lagoon (2024-present).

UCSB SONGS Mitigation Monitoring: Wetland Survey - Tidal Volumetric Flow Rate

These data describe annual estimates of tidal volumetric flow rate 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. Monitoring began in 2012 in the San Dieguito Wetlands in San Diego County, CA. The tidal volumetric flow rate into the wetland between low and high tide was sampled 24 times annually along a cross section transect of the main channel located 0.9 km from the inlet.

UCSB SONGS Mitigation Monitoring: Wetland Survey - Plant Reproductive Success

These data describe annual estimates of seed set for seven common salt marsh plant species at the San Dieguito Wetland 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. Monitoring began in 2012.

UCSB SONGS Mitigation Monitoring: Reef Survey - Kelp Size and Abundance

These data describe annual estimates of the size and abundance of giant kelp, Macrocystis pyrifera, at three subtidal reefs collected as part of the San Onofre Nuclear Generating Station (SONGS) Mitigation Monitoring Program. 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). In the summer of each year, divers counted the number of fronds > 1 m tall on each giant kelp plant encountered in five 20 m2 quadrats uniformly distributed along semi-permanent transects at each reef.

UCSB SONGS Mitigation Monitoring: Reef Survey - Fish Size and Abundance

These data describe annual estimates of the size and abundance of fish at three subtidal reefs collected as part of the San Onofre Nuclear Generating Station (SONGS) Mitigation Monitoring Program. 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). In the summer of each year, divers identified, sized, and counted species of fish along fixed transects, and in quadrats uniformly distributed at each reef.