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41 results for “vocalisations”
RookID: an annotated dataset of vocalisations produced by individually-identified rooks housed together in an outdoors aviary in France
<p>A dataset of annotated recordings of a captive colony of rooks, recorded in Strasbourg, France in 2020 and 2021. Each rook was individually identifiable with leg rings. All recordings were taken in the morning a few hours after sunrise, when the birds were most vocally active. The colony was housed outdoors, so other noises are present, including both biotic (most notably various birds, human voices, and other animals) and abiotic (mostly car and train noises).</p> <p>Audio files (.wav): recorded at 48 kHz, 16-bit using 1 to 3 Song Meter 4 recorders (Wildlife Acoustics). Each recorder had two microphone with different gains to maximise dynamic range. The files were then manually synchronised and merged into multichannel (2 to 6) files.</p> <p>Label files (.tsv): Labels corresponding to each recording (each pair has the same name), noting the time stamps and individual emitter for each vocalisation. A single observer annotated all the recordings. Only rook vocalisations from the captive colony were annotated, not other bird vocalisations or the various noises in the data. The annotations consist of tables with 5 columns: </p> <ul> <li>Source: the individual producing the vocalisation. Note that only the bird's name is indicated. "Inc" and "Pls" are special cases: the first was for when identity could not be determined, the second when multiple individuals vocalised at once in such a manner that individuals could not be separated</li> <li>Start: starting time point for the vocalisation, in seconds (determined as the earliest point when the vocalisation was heard on any channel)</li> <li>End: ending time point for the vocalisation, in seconds (determined as the last point when the vocalisation was head on any channel)</li> <li>Event: gives information for the bird's activity at the time of the vocalisation, but largely in abbreviated form. One particular case is "sing", which correspond to vocalisations part of a song bout (which are defined as sequences of different vocalisations separated by less than approximately 10 seconds).</li> <li>Comment: other observations regarding the vocalisation. These are usually not standardised compared to the Event column. One special case is for "Pls": the Comment column then bears information regarding the identity of the individuals involved.</li> </ul> <p> </p> <p>This dataset was used in our article "Acoustic detection and identification of individual rooks in field recordings using multi-task neural networks", to train neural networks to identify individual rooks. The dataset was therefore randomly split into train-validation-test datasets. For reproducibility, we provide the "splitting.csv" which contains the information pertaining to which files go in each dataset, and two scripts to do the split automatically.</p> <p>To do so: download and unpack the RookID folder somewhere on your computer, then download splitting.csv and either of the scripts to the same location. Both scripts will MOVE, not copy, the files to new folders corresponding to each dataset.</p> <ul> <li>with split_data.R: open the scrip in an RStudio environment, edit the out_path variable to the desired location, and run the script</li> <li>with split_data.py: run the following command line: python /path/to/split_data.py --out_path path/to/desired/location (note that the script will automatically create the necessary tree structure)</li> <li>Both scripts can be run without editing the out_path variables, in which case the new folders will be created at the same location</li> </ul> <p> </p> <p>For further information, see our code at <a href="https://gitlab.com/kimartin/rook-vocalisation-detection">https://gitlab.com/kimartin/rook-vocalisation-detection</a></p> <p>For any inquiries, please contact Killian Martin (<a href="mailto:killian.martin@ens-lyon.fr?subject=Inquiry%20about%20the%20RookID%20dataset">killian.martin@ens-lyon.fr</a>)</p>
Figure 5 in Nesting evidence, density and vocalisations in a resident population of Savannah Sparrow Passerculus sandwichensis wetmorei in Guatemala
Figure 5. Sonograms of songs of four male Savannah Sparrows Passerculus sandwichensis wetmorei in PRM Todos Santos Cuchumatán, dpto. Huehuetenango, Guatemala: (a) 5 June 2016 (Knut Eisermann, XC333471), including waveform, (b) 5 June 2016 (Knut Eisermann, XC333471), (c) 3 June 2016 (Knut Eisermann, XC333472), (d) 3 June 2016 (Knut Eisermann, XC333473). DW = descendent whistle. See Table 1 for signal measurements of marked notes.
Figure 4 in Nesting evidence, density and vocalisations in a resident population of Savannah Sparrow Passerculus sandwichensis wetmorei in Guatemala
Figure 4. (1) Approximate breeding range of Savannah Sparrow Passerculus sandwichensis in Mexico (sensu Howell & Webb 1995); (2) summer records in the Sierra Los Cuchumatanes, Guatemala, including recent nesting and other summer records (June–July 2016), and historic summer records (June 1897, van Rossem 1938); and (3) summer record from Sierra Madre range in June 2002 (J. Berry in Eisermann & Avendaño 2007). Chis. = Chiapas, Mexico, GT = Guatemala, HN = Honduras, SV = El Salvador. Inset map shows location of summer records of Savannah Sparrow in the Sierra Los Cuchumatanes (SLC) and Sierra Madre (SM) ranges in Guatemala.
Figure 3 in Nesting evidence, density and vocalisations in a resident population of Savannah Sparrow Passerculus sandwichensis wetmorei in Guatemala
Figure 3. Nesting evidence of Savannah Sparrow Passerculus sandwichensis wetmorei in PRM Todos Santos Cuchumatán, dpto. Huehuetenango, Guatemala: (a) nest with a single nestling, 2 July 2016 (a second nestling was found dead 20 cm from the nest); (b) recently fledged juvenile, barely able to fly, 3 July 2016, (c–d) two fledglings well able to fly, tail c.40% grown, 3 July 2016; (e) dependent juvenile with tail c.80% grown, 3 July 2016; and (f) immature, 27 August 2016 (Knut Eisermann)
Figure 2 in Nesting evidence, density and vocalisations in a resident population of Savannah Sparrow Passerculus sandwichensis wetmorei in Guatemala
Figure 2. Different adult Savannah Sparrows Passerculus sandwichensis wetmorei of a breeding population in PRM Todos Santos Cuchumatán, dpto. Huehuetenango, Guatemala: (a) lateral; (b) dorsal, 5 June 2016; and (c) frontal view showing the neatly marked median crown-stripe, 2 July 2016 (Knut Eisermann)
Figure 1 in Nesting evidence, density and vocalisations in a resident population of Savannah Sparrow Passerculus sandwichensis wetmorei in Guatemala
Figure 1. Habitat of a breeding population of Savannah Sparrow Passerculus sandwichensis wetmorei at 3,700 m in PRM Todos Santos Cuchumatán, dpto. Huehuetenango, Guatemala, 5 June 2016; the undulating landscape, shaped by glaciers during the late Quaternary, is currently covered with grassland dominated by Muhlenbergia quadridentata (Poaceae) (Knut Eisermann)
Data from: Koe: Web-based software to classify acoustic units and analyse sequence structure in animal vocalisations
<p>1. Classifying acoustic units is often a key step in studying repertoires and sequence structure in animal communication. Manual classification by eye and ear remains the primary method, but new tools and techniques are urgently needed to expedite the process for large, diverse datasets.</p> <p>2. Here we introduce <i>Koe</i>, an application for classifying and analysing animal vocalisations. <i>Koe</i> offers bulk-labelling of units via interactive ordination plots and unit tables, as well as visualisation and playback, segmentation, measurement, data filtering/exporting and new tools for analysing repertoire and sequence structure—in an integrated environment.</p> <p>3. We demonstrate <i>Koe</i> with a real-world case study of New Zealand bellbird <i>Anthornis melanura</i> songs from an archipelago metapopulation. Having classified 21,500 units in <i>Koe</i>, we compare repertoires and sequence structure between sites and sexes.</p> <p>4. <i>Koe</i> is web-based (koe.io.ac.nz) and easy to use, making it ideal for collaboration, education and citizen science. By enabling large-scale, high-resolution classification and analysis of animal vocalisations, <i>Koe</i> expands the possibilities for bioacoustics research.</p>
Data and codes: Who is calling? Optimising source identification from marmoset vocalisations with hierarchical machine learning classifiers
<p>Data and codes that accompany the article titled "Who is calling? Optimising source identification from marmoset vocalisations with hierarchical machine learning classifiers".</p>
Data from: Koe: Web-based software to classify acoustic units and analyse sequence structure in animal vocalisations
Open the record for dataset details and reuse information.
F0 estimation for bioacoustics: A benchmark/training dataset of non-human vocalisations with annotated frequency contours
Open the record for dataset details and reuse information.
Acoustic spatial capture-recapture study on vocalising bowhead whales
<h1>Acoustic spatial capture-recapture study on vocalising bowhead whales</h1> <p>Contains the code and data used for the analysis of the case study data and run the simulation study. <br>The results of this study have been peer-reviewed and published (DOI: https://doi.org/10.1007/s13253-023-00563-0) and also appear in Chapter 2 and 3 of the PhD thesis "Advancements in methods for estimating the abundance of marine megafauna using novel sampling techniques" by Felix T Petersma. <br>We provide some information in support of the files presented here; however, for extensive background we kindly refer you to the publication.</p> <p>Most of the functionality of the model fitting is contained in the 'ascrRcpp'-package. <br>This package has been included pre-built and can be installed using the file 'ascrRcpp_1.0.tar.gz'.<br>Once this package is installed, all scripts included in this location should run fine, given that all other packages that are used will be installed as well.</p> <p> </p>
DB3V: A Dialect Dominated Dataset of Bird Vocalisation for Cross-corpus Bird Species Recognition
<p>The first cross-corpus dataset that focuses on dialects in bird vocalisations. The DB3V comprises more than 25 hours of audio recordings from 10 bird species distributed across three distinct regions in the contiguous United States (CONUS).</p>
Estimating effective detection area of static passive acoustic data loggers from playback experiments with cetacean vocalisations
<p>This link provides the data from the playback experiment to determine effective detection areas for porpoises recorded by C-POD acoustic dataloggers. The firstdata set includes the artifically created porpoises click trains captured by the C-PODs and the second is the record of the rate of re-capture for the real, recorded porpoise clicks used in the experiment. </p>
TABLE 1 in Nesting evidence, density and vocalisations in a resident population of Savannah Sparrow Passerculus sandwichensis wetmorei in Guatemala
<p>TABLE 1 Mean (± SD) and range of signal characteristics of songs of breeding Savannah Sparrows <i>Passerculus sandwichensis wetmorei</i> in PRM Todos Santos Cuchumatán, dpto. Huehuetenango, Guatemala, in June 2016, <i>n</i> = 37 songs of four males.</p><table><thead><tr><th><b>Song section (see Fig. 5)</b></th><th><b>Duration (seconds)</b></th><th><b>Peak frequency (kHz)</b></th></tr></thead><tbody><tr><th>Entire song (<i>n</i> = 37)</th><td>2.5 ± 0.3 (2.1–3.1)</td><td></td></tr><tr><th>Introduction:</th><td></td><td></td></tr><tr><th><i>Chip</i> note (<i>n</i> = 97)</th><td>0.06 ± 0.01 (0.04–0.12)</td><td>7.906 ± 202 (6.938 –8.250)</td></tr><tr><th>Middle section:</th><td></td><td></td></tr><tr><th>Descending whistle (DW1) (<i>n</i> = 37)</th><td>0.10 ± 0.01 (0.08–0.11)</td><td>6.927 ± 132 (6.750 –7.125)</td></tr><tr><th>Trill (n = 37)</th><td>0.05 ± 0.01 (0.03–0.06)</td><td>6.471 ± 1.268 (4.125 –7.500)</td></tr><tr><th>Double <i>ch</i> note (<i>n</i> = 37)</th><td>0.08 ± 0.004 (0.07–0.10)</td><td>5.063 ± 378 (3.188 –5.625)</td></tr><tr><th>Dominant section:</th><td></td><td></td></tr><tr><th>Buzz (<i>n</i> = 37)</th><td>0.60 ± 0.06 (0.5–0.8)</td><td>6.456 ± 646 (4.688 –6.938)</td></tr><tr><th>Terminal section:</th><td></td><td></td></tr><tr><th>Descending whistle (DW2) (<i>n</i> = 37)</th><td>0.08 ± 0.005 (0.07–0.09)</td><td>7.566 ± 222 (7.313 –8.063)</td></tr><tr><th>Trill-whistle (n = 37)</th><td>0.29 ± 0.07 (0.16 – 0.39)</td><td>4.074 ± 355 (3.375 –4.313)</td></tr></tbody></table>
Data from: Vocalisations of killer whales (Orcinus orca) in the Bremer Canyon, Western Australia
To date, there has been no dedicated study in Australian waters on the acoustics of killer whales. Hence no information has been published on the sounds produced by killer whales from this region. Here we present the first acoustical analysis of recordings collected off the Western Australian coast. Underwater sounds produced by Australian killer whales were recorded during the months of February and March 2014 and 2015 in the Bremer Canyon in Western Australia. Vocalisations recorded included echolocation clicks, burst-pulse sounds and whistles. A total of 28 hours and 29 minutes were recorded and analysed, with 2376 killer whale calls (whistles and burst-pulse sounds) detected. Recordings of poor quality or signal-to-noise ratio were excluded from analysis, resulting in 142 whistles and burst-pulse vocalisations suitable for analysis and categorisation. These were grouped based on their spectrographic features into nine Bremer Canyon (BC) "call types". The frequency of the fundamental contours of all call types ranged from 600 Hz to 29 kHz. Calls ranged from 0.05 to 11.3 seconds in duration. Biosonar clicks were also recorded, but not studied further. Surface behaviours noted during acoustic recordings were categorised as either travelling or social behaviour. A detailed description of the acoustic characteristics is necessary for species acoustic identification and for the development of passive acoustic tools for population monitoring, including assessments of population status, habitat usage, migration patterns, behaviour and acoustic ecology. This study provides the first quantitative assessment and report on the acoustic features of killer whales vocalisations in Australian waters, and presents an opportunity to further investigate this little-known population.
FIGURE 9 in Remarks on biology, vocalisations and systematics of Urocynchramus pylzowi Przewalski (Aves, Passeriformes)
FIGURE 9. Single song phrases of U. pylzowi (if not mentioned all recordings by Axel Gebauer, same place as in Fig. 2). A: quiet type with rosefinchlike rhythm (09/06/1990); B: loud type of individual I (09/06/1990); C: loud type of individual II (09/06/1990); D: loud type of individual III (recorded by Per Alström, Koko Nor, May 1987, BLOWS No. pa31); E: loud type of individual IV (10/06/1996); F: loud type of individual V (19/06/1996).
FIGURE 13 in Remarks on biology, vocalisations and systematics of Urocynchramus pylzowi Przewalski (Aves, Passeriformes)
FIGURE 13. Comparison of songs. U. pylzowi (recording: Axel Gebauer, Qinghai Nanshan, 09/06/ 1990). Uragus sibiricus (recording: Dieter Wallschläger, Mongolia, WestChentej, Tereldsh, 01/06/ 1983). Carpodacus rubicilloides (recording: Paul Holt, Qinghai Nanshan, 29/05/1993, BLOWS No. 44823). Emberiza schoeniclus (recording: Axel Gebauer, Germany, Saxony, Dürrbach, 25/03/ 2005).
FIGURE 2 in Remarks on biology, vocalisations and systematics of Urocynchramus pylzowi Przewalski (Aves, Passeriformes)
FIGURE 2. Breedinghabitat of U. pylzowi with flowering Potentilla fruticosa, Qinghai Nanshan south edge of Qinghai Hu near Heimahé (36°50´N/99°38´E). Photograph Axel Gebauer (26/06/ 1998).
FIGURE 7 in Remarks on biology, vocalisations and systematics of Urocynchramus pylzowi Przewalski (Aves, Passeriformes)
FIGURE 7. Calls of U. pylzowi (if not mentioned all recordings by Axel Gebauer, same place as in Fig. 2). A: contact while preening (09/06/1990); B: contact while feeding (recorded by Herbert Nickel, Qinghai Nanshan, 1988); C: contact within a song (09/06/1990); D: before starting to flight (10/06/1996); E: male chasing a congener (09/06/1990).
FIGURE 11 in Remarks on biology, vocalisations and systematics of Urocynchramus pylzowi Przewalski (Aves, Passeriformes)
FIGURE 11. Phrases of a perch song of U. pylzowi (individual IV, recorded by Axel Gebauer, Qinghai Nanshan, 05/06/1990).
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