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201 results for “singing”
Data from: Vocal repertoire expansion in singing mice by co-opting a conserved midbrain circuit node
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Can behaviour impede evolution? persistence of singing effort after morphological song loss in crickets
<p>Evolutionary loss of sexual signals is widespread. Examining the consequences for behaviours associated with such signals can provide insight into factors promoting or inhibiting trait loss. We tested whether a behavioural component of a sexual trait, male calling effort, has been evolutionary reduced in silent populations of Hawaiian field crickets (<em>Teleogryllus oceanicus</em>). Cricket song requires energetically costly wing movements, but 'flatwing' males have feminised wings that preclude song and protect against a lethal, eavesdropping parasitoid. Flatwing males express wing movement patterns associated with singing but, in contrast to normal-wing males, sustained periods of wing movement cannot confer sexual selection benefits and should be subject to strong negative selection. We developed an automated technique to quantify how long males spend expressing wing movements associated with song. We compared calling effort among populations of Hawaiian crickets with differing proportions of silent males, and between male morphs. Contrary to expectation, silent populations invested as much in calling effort as non-silent populations. Additionally, flatwing and normal-wing males did not differ in calling effort. The lack of evolved behavioural adjustment following morphological change in silent Hawaiian crickets illustrates how behaviour might sometimes impede, rather than facilitate, evolution.</p>
Data from: Singing behaviour of Ruby-crowned Kinglets (Regulus calendula) in relation to time-of-day, time-of-year, and social context
Observational field studies provide insight on the multifunctional nature of birdsong. For example, if song production were limited to pre-fertilization, then that would suggest a mate attraction function. If it were used throughout the breeding season and in response to intruding males, then that would suggest a territorial defence function. In the present study, we determined the daily and seasonal singing patterns of male Ruby-crowned Kinglets (Regulus calendula) in Labrador, Canada, using microphone arrays in two breeding seasons. Using a playback experiment, we simulated a territorial intrusion to compare the structure of songs produced while defending a territory to the structure of songs produced during solo and contest singing. Singing peaked in the early part of the breeding season and then declined continuously for the remainder of the season, which suggests that the songs function in mate attraction. Singing peaked 2-3 h after dawn, and then declined steadily until it stopped at 2200 h. Some nocturnal singing was observed, but no dawn singing was observed. A high probability of signal overlap by heterospecific songs at dawn would hinder signal recognition and explain the observed delay in peak singing activity. Vocal responses to playback suggested a function in territory defence. However, there were no significant differences in the duty cycle, frequency modulation, and bandwidth of songs in relation to the context of song production, though songs were shorter in the intrusion context than during solo singing. Overall, the study provides the first quantitative description of the effects of time of day, time of year, and social context on singing behaviour in this understudied species.
Statuette of a Singing Monkey
Statuette of a Singing Monkey of the "Monkey Orchestra" series ID no.: ZKWawel 5127 http://muzea.malopolska.pl/en/obiekty/-/a/4869610/4877253 Museum: Wawel Royal Castle – State Art Collection Digitalisation: RDW MIC, Małopolska's Virtual Museums Plus project Source: Objaverse 1.0 / Sketchfab
Nepali singing bowl
Nepali singing bowl https://bestsingingbowls.com/history-singing-bowls/ https://www.antiquesingingbowls.com/about/antique-singing-bowls.html Source: Objaverse 1.0 / Sketchfab
Tibetan Singing Bowl
Tibetan Singing Bowl made of bronze, purchased from Golden Temple Singing Bowls and Healing Center (in Nepal) Also known as the [Standing Bell](https://en.wikipedia.org/wiki/Standing_bell), used for religous (Buddhist) and ["spiritual" healing exercises](https://journals.sagepub.com/doi/full/10.1177/2156587216668109) We use it mostly as an interactive / decorative centerpiece #opensourcesarawak Source: Objaverse 1.0 / Sketchfab
Singing silver-haired bats (Lasionycteris noctivagans)
<p class="MsoNormal">Characterizing sounds produced by animals can lead to better understanding of their behavioral ecology and conservation. While considerable focus has been on signals used by bats for echolocation, there has been less emphasis on nonecholocation sounds. We describe songs (i.e., acoustic vocalizations with distinctive syllable types in series or in complex motifs) produced by silver‐haired bat (<em>Lasionycteris noctivagans</em>). Songs, characterized by a sequence (song phrase) of 3 distinct vocalization types, were confirmed by observing free‐flying, silver‐haired bats at mine hibernacula in British Columbia, Canada. The song patterns were relatively consistent with each song phrase consisting of a lead call, followed by a droplet call, and finishing with a series of multiple chirp calls. The function of the songs is unknown, however, as other bat species produce songs for mating, we propose silver‐ aired bat songs may similarly be associated with courtship or mating. Alternative functions cannot be ruled out, particularly because we recorded some songs outside of the accepted mating period. Other research has determined peak mating of silver‐haired bats occurs in fall, and spring mating has been documented. Here we additionally provide evidence of winter mating in British Columbia. The proportion of silver‐haired bat songs recorded relative to echolocation recordings varied across locations and seasons. While we recorded songs in all months of the year, more than half of the songs were produced during winter, and 93.4% (of 1,857) were produced outside of summer months. Song production in summer could be associated with other behaviors such as learning or practice, establishing or maintaining social bonds, or male‐male competition. To provide landscape and temporal context, we summarize acoustic datasets from numerous locations in western North America where recordings were made between 2005 and 2022.</p>
Communal Singing in Denmark 2022
<p>This comprehensive dataset is derived from a large-scale survey focused on communal singing (<em>fællessang</em>) in Denmark. Recently, this cultural practice has garnered significant attention, especially during the COVID-19 lockdowns. Despite its growing prominence, there has been a lack of empirical data concerning the extent, diversity, contexts, and perceptions surrounding communal singing in Denmark—until now. The dataset, compiled from responses of 2,031 Danish adults in October 2022 through a collaboration with YouGov Denmark, offers valuable insights into the current state of singing practices and attitudes among the Danish population. This dataset forms the basis for ongoing research projects and forthcoming publications by the Unit for Song Studies at Aarhus University. The dataset contains a detailed spreadsheet of the survey's comprehensive findings.</p>
SVDD Challenge 2024: A Singing Voice Deepfake Detection Challenge (WildSVDD Track)
<p>For more information about SVDD Challenge 2024, please refer to https://challenge.singfake.org/.<br><br>WildSVDD track dataset is an extension of <a href="https://singfake.org/">SingFake</a> dataset. </p>
Underlying REVISED dataset for the study: Singing and music making: Physiological responses across early to later stages of dementia
<p>These files contain the REVIDED underlying data for the study, Singing and Music Making: Physiological Responses Across Early to Later Stages of Dementia; physiological data from Study 1 and Study 2, and video recording engagement scores from Study 2.</p> <p><strong>in Study 2, the electrodermal readings (EDA) for the Slow Music readings in session 1 had become corrupted. The correct EDA data for this session was uploaded on 31.3.24.</strong></p> <p>The project was funded by the Wellcome Trust as part of The Hub Award at the Wellcome Collection, London. The article that these data are based on can be here: https://wellcomeopenresearch.org/articles/6-150/v1, Wellcome Open Research, 6:150.</p> <p>The abstract from the accompanying article:</p> <p><strong>Background</strong>: Music based interventions have been found to improve the wellbeing of people living with dementia. Research to date has primarily used psychometric questionnaires and qualitative interviews to determine impact and efficacy. More recently there has been an interest in exploring if psychophysiological measures could provide additional information about how music, singing and other arts activities impact this population. Physiological responses can provide additional evidence about an individual’s experience of an activity and may be particularly useful for people who are experiencing difficulties with communication. </p> <p><strong>Methods:</strong> This multiple-case study design drew on previously collected, unanalysed archival data and explored the physiological responses of nine people with mild-to-moderate dementia during a singing group, and six people in the later stages of dementia during an interactive music group. Medical grade Empatica E4 ™ wearable wristbands provided information on heart rate (HR), electrodermal activity (EDA), movement (ACC) and skin temperature (ST). The interactive music group was video recorded using non-intrusive Fly 360-degree cameras™ in order to provide additional group interactive information about engagement. </p> <p><strong>Results</strong>: Physiological responses were analysed using simulation modelling analysis (SMA) within individual case studies. Participants in the singing group showed an increase in EDA and HR as the session began. HR and ST increased during faster paced songs. EDA, movement and engagement were all higher during an interactive music group than during a control session (music listening). EDA and ST increased and in contrast to the responses during singing, HR decreased as the sessions began. EDA was higher during slower music, however this was less consistent in the more interactive intervention sessions than the control. There were no consistent changes in HR and movement responses during different styles of music. Physiological responses peaked during familiar music, interactions, physical touch in addition to times that participants appeared disengaged. </p> <p><strong>Conclusion</strong>: Non-intrusive physiological measures obtained from easily worn wristband devices may provide valuable information about the experiences of people living with dementia who participate in arts and other activities, particularly for those in later stages when verbal communication may be more difficult and it is no longer possible to complete psychometric questionnaires. However, whenever feasible, they should be used in conjunction with other measures to develop a more nuanced understanding of these experiences. Future research should consider using physiological measures with video-analysis and observational measures, where possible, to explore further how engagement in specific activities, wellbeing and physiology interact. This may provide valuable information for further development of activities and services for those living with dementias across different levels of impairment.</p>
Singing strategies are linked to perch use on foraging territories in heart-nosed bats
<p>These data include the GPS data of 14 VHF telemetry tracked heart-nosed bats (<em>Cardioderma cor</em>) and associated singing behavior collected during the long dry season (May to October) in Tanzania. These data were used to establish that singing occurs on nighttime foraging areas, and that foraging areas are exclusive and repeatedly used, supporting the hypothesis that <em>C. cor</em> maintain individualistic foraging territories with singing. Times and locations of singing are included in the data set and linked to the GPS waypoints of perches individuals used repeatedly during then 4-6 nights of tracking. GPS data is organized by list of separate waypoints and whether they were used for singing. Furthermore, individuals sit in trees and sing for long stretches of time, and thus these durations were subsampled into 2 minute intervals and associated with the perch location to create a dateset of points for Kernal Density Estimates. Times and perch locations for KDE, including associated singing behavior, are also included. Finally, singing duration of each individual is broken down by perch, night, and hour. Of the 14 tracked individuals, 13 are male (one of which stopped singing soon after tracking commenced) and one is a nonsinging female. </p>
FIG. 3 in When did roosters start singing at Arslantepe? A preliminary assessment of the presence and spread of Gallus gallus (Linnaeus, 1758) in Iron Age Eastern Anatolia
FIG. 3. — Arslantepe, level IIIB. Credits: G. Liberotti, © MAIAO.
FIG. 2 in When did roosters start singing at Arslantepe? A preliminary assessment of the presence and spread of Gallus gallus (Linnaeus, 1758) in Iron Age Eastern Anatolia
FIG. 2. — Arslantepe, the Iron Age monumental sequence. Photo credits: R. Ceccacci, ©MAIAO.
Vermilion flycatchers avoid singing during sudden peaks of anthropogenic noise
<p>Data from a playback experiment where we showed that vermilion flycatchers stop singing when experiencing an increase in sudden urban noise, and resume singing showing full vocal recovery after that. This could be an uncommon strategy to enhance information transfer in environments where noise amplitude fluctuates rapidly</p>
Data for: Individual differences in song plasticity in response to social stimuli and singing position
<p>Individual animals can react to the changes in their environment by exhibiting behaviours in an individual-specific way leading to individual differences in phenotypic plasticity. However, the effect of multiple environmental factors on multiple traits is rarely tested. Such a complex approach is necessary to assess the generality of plasticity and to understand how among-individual differences in the ability to adapt to changing environments evolve. This study examined whether individuals adjust different song traits to varying environmental conditions in the collared flycatcher (Ficedula albicollis), a passerine with complex song. We also aimed to reveal among-individual differences in behavioural responses by testing whether individual differences in plasticity were repeatable. The presence of general plasticity across traits and/or contexts was also tested. To assess plasticity, we documented 1) short-scale temporal changes in song traits in different social contexts (after exposition to male stimulus, female stimulus or without stimuli), and 2) changes concerning the height from where the bird sang (singing position), used as a proxy of predation risk and acoustic transmission conditions. We found population-level relationships between singing position and both song length and complexity, as well as social context-dependent temporal changes in song length and maximum frequency. We found among-individual differences in plasticity of song length and maximum frequency along both the temporal and positional gradients. These among-individual differences in plasticity were repeatable. Some of the plastic responses correlated across different song traits and environmental gradients. Overall, our results show that the plasticity of bird song 1) depends on the social context, 2) exists along different environmental gradients and 3) there is evidence for trade-offs between the responses of different traits to different environmental variables. Our results highlight the need to consider individual differences and to investigate multiple traits along multiple environmental axes when studying behavioural plasticity. </p>
singing nepali bowl - animation
Small animation with sound of nepali singing bowl More about singing bowls: https://bestsingingbowls.com/history-singing-bowls/ https://www.antiquesingingbowls.com/about/antique-singing-bowls.html Source: Objaverse 1.0 / Sketchfab
Dataset for Interspeech 2018 submission: Singing voice phoneme segmentation by hierarchically inferring syllable and phoneme onset positions
<p>This dataset contains the materials for training, testing the joint and HSMM models mentioned in the paper "<em>Singing voice phoneme segmentation by hierarchically inferring syllable and phoneme onset positions"</em>.</p> <p>The filename list of this dataset can be found in the function <em>get_train_test_recordings_joint()</em> of <em>./general/trainTestSeparation.py</em> file. The dataset contains the Praat TextGrids and .wavs of the variables: <em>train_primary_school, val_primary_school</em> and <em>test_primary_school</em>. For accessing other datasets such as <em>train_nacta_2017, train_nacta</em> and <em>train_sepa</em>, please download them from the links:</p> <p>jingju dataset part1: <a href="https://zenodo.org/record/1185154">https://zenodo.org/record/1185154</a></p> <p>jingju dataset part2: <a href="https://doi.org/10.5281/zenodo.842229">https://doi.org/10.5281/zenodo.842229</a></p> <p>Once you have downloaded these three datasets, you need to set the paths in <em>./general/filePathShared.py</em>.</p> <p>Set <em>path_jingju_dataset</em> to the parent path of these three datasets.</p> <p>Set <em>primarySchool_dataset_root_path</em> to the path of the interspeech2018 dataset (the current dataset).</p> <p>Set <em>nacta_dataset_root_path</em> to the path of the jingju dataset part1.</p> <p>Set <em>nacta2017_dataset_root_path</em> to the path the jingju dataset part2.</p> <p>For more information on this paper, please refer to the Github page: <a href="https://github.com/ronggong/interspeech2018_submission01">https://github.com/ronggong/interspeech2018_submission01</a></p> <p> </p>
Jingju a cappella singing dataset part3
<p>这是京剧清唱数据库的第三部分。这个部分集中于音乐教育的应用。对每个唱段,我们采集了老师和学生的录音。</p> <p>This is the 3rd part of the jingju a cappella singing dataset. This part focus on the music education application. For this purpose, we collected both "teacher" and "students" recordings for each aria.</p> <p><strong>文件 Files:</strong></p> <ol> <li>wav_left.zip: audio files in .wav format, mono</li> <li>textgrid.zip: line, syllable and phoneme time boundaries and labels, in Praat .textgrid format</li> <li>annotation_txt.zip: line, syllable and phoneme time boundaries and labels, in .txt format <ol> <li>*phrase_char: phrase-level time boundaries, labeled in Mandarin characters</li> <li>*phrase: phrase-level time boundaries, labeled in Mandarin pinyin</li> <li>*syllable: syllable-level time boundaries, labeled in Mandarin pinyin</li> <li>*phoneme: phoneme-level time boundaries, labeled in X-SAMPA</li> </ol> </li> <li>arias.ods: spreadsheet containing the detailed information of each recording -- role-type, shengqiang, banshi, singer and melodic line, syllable, phoneme numbers.</li> </ol> <p> </p> <p><strong>艺术家 Artists:</strong></p> <p>示范录音取自3位年轻的专业京剧演员。学生录音取自几位非专业小学生和非艺术类大学的学生。</p> <p>Teacher recordings are recorded by 3 professional young jingju performers. Student recordings are performed by several non-jingju professional primary school students and some non-art university students. </p> <p> </p> <p><strong>标注 Annotation:</strong></p> <p>数据库包含一部分录音的唱句起始位置和音节起始位置标注,标注格式为Praat TextGrid。唱句标注包含有每一唱句的歌词,此歌词从曲谱提取,并不与实际演唱一致;音节标注包含拼音,音素标注为X-SAMPA,经过作者修正,试图与演唱发音一致。</p> <p>The dataset contains the line and syllable boundary annotation for a part of recordings, in Praat TextGrid format. The line annotation contains the lyrics for each line, which is extracted from the score, and might not coherent with the actual singing; the syllable annotation contains pinyin, phoneme annotation uses X-SAMPA, corrected by the author to be coherent with the actual singing.</p> <p>标注X-SAMPA格式和其他信息可以参考以下链接:</p> <p>Annotation format, units, parsing code and other information please refer to:</p> <p><a href="https://github.com/MTG/jingjuPhonemeAnnotation">https://github.com/MTG/jingjuPhonemeAnnotation</a></p> <p> </p> <p><strong>协议 License:</strong></p> <p><a href="https://creativecommons.org/licenses/by-nc/4.0/">Creative Commons Attribution-NonCommercial 4.0</a></p> <p> </p> <p><strong>联系方式 Contact information</strong>:</p> <p><em>如果任何问题,请联系作者 </em><em>If you have any question, please contact the author:</em></p> <p>龚嵘 Rong Gong: Email - rong<dot>gong<at>upf<dot>edu, Wechat id - gongr86</p>
Jingju a cappella singing voice test dataset for "An efficient deep learning model for musical onset detection"
<p>Jingju a cappella singing voice test dataset used in the paper "An efficient deep learning model for musical onset detection".</p> <p>Arxiv paper link: <a href="https://arxiv.org/abs/1806.06773">https://arxiv.org/abs/1806.06773</a></p> <p>Supplementary information and code for the paper: <a href="https://github.com/ronggong/musical-onset-efficient">https://github.com/ronggong/musical-onset-efficient</a></p> <p><strong>Content:</strong></p> <ol> <li>ismir_2018_dataset_for_reviewing.zip: audio, syllable boundary and label annotation</li> <li>jingju dataset train test split filenames.xlsx: train and test split filename list</li> </ol> <p><strong>Citation:</strong></p> <pre>@article{gong2018towards, title={Towards an efficient deep learning model for musical onset detection}, author={Gong, Rong and Serra, Xavier}, journal={arXiv preprint arXiv:1806.06773}, year={2018} } </pre> <p><strong>Contact:</strong></p> <p>Rong Gong: rong.gong<at>upf.edu</p>
Data from: Change in singing behavior of humpback whales caused by shipping noise (Tsujii et al., 2018)
<p>Audio (.wav) and comma-delimited text format (.csv) files are contained. <br> This dataset was used in the study, which was submitted in 2018 to PLOS ONE for publication:</p> <p>Koki Tsujii, Tomonari Akamatsu, Ryosuke Okamoto, Kyoichi Mori, Yoko Mitani, Naoya Umeda.<br> Change in singing behavior of humpback whales caused by shipping noise.</p> <p>This dataset was obtained in the research activity of underwater noise project of the Japan Ship Technology Research Association in the fiscal years of 2016 funded by the Nippon Foundation.</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)
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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
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