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693 results for “vocalizations”
Nonlinear vocal phenomena in the begging calls of the African penguin
<p>This repository hosts the dataset used in the analysis conducted for the article titled "Nonlinear Vocal Phenomena in the Begging Calls of the African Penguin," including all the necessary files to replicate the analysis and findings presented in the study.</p> <p> </p> <p><strong>Files information</strong></p> <ul> <li><strong>Dataset_full_model.csv = model 1</strong><br>The variable inside are: <br>file_ name= name of the file <br>seq= sequences' Identity<br>id = chicks' identity<br>status = healthy or sick<br>age = chicks age in day<br>nlp= presence/absence<br><br></li> <li><strong>Dataset_control_model.csv = model 2</strong><br>file_ name= name of the file <br>seq= sequences' Identity<br>id = chicks' identity<br>status = healthy or sick<br>age = chicks age in day<br>nlp= nlp presence/absence<br><br></li> <li><strong>Dataset_reduced_NLP_category.csv = model 3, model 4, model 5</strong><br>file_ name= name of the file <br>seq= sequences' Identity<br>id = chicks' identity<br>status = healthy or sick<br>age = chicks age in day<br>nlp_ch=nlp chaos presence/absence<br>nlp_sb=nlp sidebands presence/absence<br>multi = presence of subharmonics, frequency jump or both<br><br></li> <li><strong>Dataset_reduced_NLP_duration.csv = model 6</strong><br>file_ name= name of the file <br>seq= sequences' Identity<br>id = chicks' identity<br>status = healthy or sick<br>age = chicks age in day<br>freq= duration of the NLP normalised on the call duration</li> </ul> <p> </p>
Nonlinear vocal phenomena in African penguin begging calls: occurrence, significance, and potential applications
<p>This repository hosts the dataset used in the analysis conducted for the article titled "Nonlinear vocal phenomena in African penguin begging calls: occurrence, significance, and potential applications" including all the necessary files to replicate the analysis and findings presented in the study.</p> <p> </p> <p><strong>Files information</strong></p> <ul> <li><strong>Dataset_full_model.csv = model 1</strong><br>The variable inside are: <br>file_ name= name of the file <br>seq= sequences' Identity<br>id = chicks' identity<br>status = healthy or sick<br>age = chicks age in day<br>nlp= presence/absence<br><br></li> <li><strong>Dataset_control_model.csv = model 2</strong><br>file_ name= name of the file <br>seq= sequences' Identity<br>id = chicks' identity<br>status = healthy or sick<br>age = chicks age in day<br>nlp= nlp presence/absence<br><br></li> <li><strong>Dataset_reduced_NLP_category.csv = model 3, model 4, model 5</strong><br>file_ name= name of the file <br>seq= sequences' Identity<br>id = chicks' identity<br>status = healthy or sick<br>age = chicks age in day<br>nlp_ch=nlp chaos presence/absence<br>nlp_sb=nlp sidebands presence/absence<br>multi = presence of subharmonics, frequency jump or both<br><br></li> <li><strong>Dataset_reduced_NLP_duration.csv = model 6</strong><br>file_ name= name of the file <br>seq= sequences' Identity<br>id = chicks' identity<br>status = healthy or sick<br>age = chicks age in day<br>freq= duration of the NLP normalised on the call duration</li> </ul> <p> </p>
DAMP-VP1k: Digital Archive of Mobile Performances - Smule Vocal Performances 100x10
<p>Digital Archive of Mobile Performance DAMP-VP1k archive of Smule vocal performances, 100 singers, 10 Performance each.</p> <p>The dataset contains sung musical performances from the Smule app. Data files include audio.zip with all the compressed audio files, and metadata.csv describing some metadata about each performance, including unique identifiers for each recording, song, and singer, as well as binary gender labels, region labels, and social "love" counts from the Smule app.</p> <p>This archive is a subset of the DAMP-Multiple Songs archive hosted at https://ccrma.stanford.edu/damp/, which contains multiple performances from each of multiple singers, singing different songs, without much verification of the data. This subset has been reduced to a subset of 10 performances per singer, with cleaner recordings for each singer preselected.</p> <p>Users of this dataset must read and accept Smule's Research Data License Agreement (LICENSE.txt).</p>
DAMP-VPB: Digital Archive of Mobile Performances - Smule Vocal Performances Balanced
<p>The DAMP-balanced dataset contains 24874 solo singing performances from 5429 singers singing a collection of 14 songs.<br> The structure of the DAMP-balanced is that the last 4 songs are designed to be the test set, and the first 10 songs<br> could be partitioned into any 6/4 train/validation split (permutation) that the singers in train and validation set sang<br> the same 6/4 songs collections according to the 6/4 split (the number of total recordings for train and validation set<br> are different from split to split, since there are different number of singers that all sang the same 6/4 split for<br> different split).</p> <p>For example, a subset from the dataset splitting the 14 songs into 6/4/4 train/validation/test sets having 276/88/224<br> performances sang by 46/22/56 singers could be extracted from the dataset and be used for machine learning tasks.<br> Each singer in the train, validation and test set, sang each of the 6/4/4 songs once respectively, thus making the<br> collections of performances "balanced" respect to the song collections.</p> <p>List of songs:</p> <ol> <li>one call away - Charlie Puth(3912)</li> <li>say you won`t let go - James Arthur(3255)</li> <li>allof me - John Legend(2856)</li> <li>closer -The Chainsmokers(2873)</li> <li>seven years - Lukas Graham(2942)</li> <li>despacito- Luis Fonsi(1287)</li> <li>more than words - Extreme(586)</li> <li>lostboy - Ruth B.(1183)</li> <li>loveyourself - Justin Bieber(3019)</li> <li>rockabye- Clean Bandit(2737)</li> <li>part of your world - Jodi Benson(56)</li> <li>when I was your man - Bruno Mars(56)</li> <li>chandelier- Sia(56)</li> <li>cups - Anna Kendrick(56)</li> </ol> <p>Users of this dataset must read and accept Smule's Research Data License Agreement (LICENSE.txt).</p>
DAMP-VSEP: Smule Digital Archive of Mobile Performances - Vocal Separation
<p>This dataset contains audio content for performing vocal separation research. It contains performances with (1) backing tracks, (2) one or more isolated vocals files, and (3) a mixture of the two. This is a real-world dataset from performances on the Smule app, which includes non-linear effects processes on the mixture of vocals and backing track. The dataset contains data from 155 countries, 36 languages, 6456 artists, and 11494 compositions.</p> <p>Users of this dataset must read and accept Smule's Research Data License Agreement (LICENSE.txt).</p>
DAMP-MVP: Digital Archive of Mobile Performances - Smule Multilingual Vocal Performance 300x30x2
<p>The Smule 300x30x2 dataset contains recordings of sung karaoke tracks, lyrics text files, and some metadata describing the songs being performed by each singer. This dataset was collected from performances on Smule by selecting the most popular singers, female and male, of the 300 most popular arrangements in 30 countries.</p> <p>The most popular arrangements were determined by counting song starts or joins (duet/group) of recordings for each arrangement, within the country of interest. The term "arrangement" is used, because there might be multiple arrangements of the same song.</p> <p>The most popular performances and singers of those arrangements were determined by counting Listens (and/or Loves, if no complete Listens) for all performances of each arrangement.</p> <p>Users of this dataset must read and accept Smule's Research Data License Agreement (LICENSE.txt).</p>
Cell type specializations of the vocal-motor cortex in songbirds
GEO Series GSE233643. Taeniopygia guttata. 2 samples. Type: Expression profiling by high throughput sequencing.
vocal-6
<p> clean voice of 6 singer for singer identification from Shanghai Conservatory of Music</p>
The Hume Vocal Burst Competition Dataset (H-VB) | Raw Data [A-VB: updated 03.01.22]
<p>This package includes the raw data for a subset of The Hume Vocal Burst Database (H-VB).</p> <p>This dataset contains <strong>59,201 audio recordings of vocal bursts from 1,702 speakers</strong>, from 4 cultures, the <strong>U.S.A, South Africa, China, </strong>and<strong> Venezuela</strong>, ranging in age from <strong>20 to 39.5 years old</strong>.</p> <p>The total duration of data in this version of <strong>H-VB is 36 Hours </strong> (Mean: 02.23 sec). A subset of 10 emotional intensity labels is also available. Data has been partitioned into equal training, validation, and test sets, and the test set is blind. </p> <p><strong>Emotion Labels: </strong><br> <em>Awe, Excitement, Amusement, Awkwardness, Fear, Horror, Distress, Triumph, Sadness, Surprise, Valence, Arousal</em></p> <p>For further questions about the data contact: <strong>competitions@hume.ai</strong></p>
VocalMind: A Stereotactic EEG Dataset for Vocalized, Mimed, and Imagined Speech in Tonal Language
Open the record for dataset details and reuse information.
Expression data from rat vocal fold at different periods after vocal fold injury (miRNA)
GEO Series GSE147473. synthetic construct; Rattus norvegicus. 20 samples. Type: Non-coding RNA profiling by array.
Defining Secure DevOps and the Missing Global Dimension: A Multi-vocal Literature Review
<p>Data and associated materials</p>
Data from "Evidence for a vocal signature in the rat and its reinforcing effects"
<p>Data from "Evidence for a vocal signature in the rat and its reinforcing effects"</p>
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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)
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.