DOI: 10.5281/zenodo.3991714
title: Automated detection of Hainan gibbon calls for passive acoustic monitoring

description: Data accompanying the paper: "Automated detection of Hainan gibbon calls for passive acoustic monitoring" <strong>Please cite this dataset as:</strong> Dufourq, Emmanuel and Durbach, Ian and Hansford, James and Hoepfner, Amanda and Ma, Heidi and Bryant, Jessica and Stender, Christina and Li, Wenyong and Liu, Zhiwei and Chen, Qing and Zhou, Zhaoli and Turvey, Samuel. (2020). Automated detection of Hainan gibbon calls for passive acoustic monitoring. BioRxiv doi: https://doi.org/10.1101/2020.09.07.285502 The Hainan gibbon is the world's rarest primate and one of the world's rarest mammals, with only a single population of about 30 individuals surviving in Bawangling National Nature Reserve (BNNR), Hainan, China. Eight Song Meter SM3 recorders (Wildlife Acoustics, Maynard, Massachusetts) were used to collect acoustic data from 1 March to 20 August 2016 within BNNR. Recorders were attached to trees at approximately 1.5 meters from the ground in tropical evergreen forest. Recorders were set to record for eight hours each day from the time of sunrise, which varied between approximately 05:00 and 06:00 during the study period. Devices did not record continuously throughout the entire survey period due to logistical and technical issues; in total, survey days per recorder varied between 79 and 129 days, and roughly 6,000 hours of recordings were collected. The majority of recordings were made with a sampling rate of 9,600Hz and bit depth of 16, with isolated recordings at 28,800Hz. We provide the audio data (.wav) used to train and test our neural network classifier along with the corresponding labelled text files (.data). <strong>Files provided</strong> Train.zip - contains the training .wav audio files Train_Labels.zip - contains the labels for the training data Test.zip - contains the testing .wav audio files Test_Labels.zip - contains the labels for the test data Extra_Labelled_Data.zip - contains extra data that was labelled and non-gibbon calls used for training Extra_Labels.zip - contains the labels for the extra labelled data Unlabelled_Data.zip - contains additional .wav audio files which have not been labelled. These are split into various files (1-15) and can be downloaded individually. Code.zip - contains all the software scripts and notebooks Manual-zip - contains the user manual <strong>Labels</strong> The names of the labelled files start with either "g_" or "n_", for example "g_HGSM3D_0+1_20160429_051600.data" and "n_HGSM3D_0+1_20160429_051600.data". Files starting with "g_" contain the timestamps of the gibbon calls, and files starting with "n_" contain the timestamps of non-gibbon calls (e.g. background noise and bird calls). An audio file will have both a "g_" and "n_" file. Each file has the following format: Start,End,Duration,Type,Notes, where "start" denotes the start time in seconds, "end" denotes the end time in seconds, "duration" denotes the duration (end - start) in seconds, "type" denotes the type of call/noise and "notes" are additional notes which we labelled. <strong>Types</strong> The legend for the "type" column in the labelled files is defined as follows. The types for gibbon and non-gibbon files are different and we distinguish this below. Gibbon files ("g_") type 1 = one pulse gibbon call type 2 = multiple pulse gibbon call (check "notes column" below) type 3 = duet gibbon call <em>Notes column (only available in gibbon files)</em> One of the following: 2 pulse call, 3 pulse call, 4 pulse call, 5 pulse call or 6 pulse call. Non-gibbon files ("n_") type 1 = rain type 2 = other species (e.g. birds) type 3 = rain and other species type 4 = rain and external noise (e.g. aircraft) type 5 = natural sounds and external noise type 6 = natural sounds and other species <strong>Training files (containing gibbon calls):</strong> HGSM3AC_0+1_20160309_055600<br> HGSM3AC_0+1_20160312_055400<br> HGSM3A_0+1_20160304_060000<br> HGSM3BD_0+1_20160305_060000<br> HGSM3AC_0+1_20160314_055200<br> HGSM3B_0+1_20150616_050500<br> HGSM3BD_0+1_20160402_053600<br> HGSM3D_0+1_20160429_051600<br> HGSM3B_0+1_20160305_060000<br> HGSM3C_0+1_20160501_051500<br> HGSM3SOL_0+1_20160320_054700<br> HGSM3SOL_0+1_20160405_053400<br> HGSM3BD_0+1_20160401_053700 <strong>Testing files:</strong> HGSM3B_0+1_20160323_054500<br> HGSM3B_0+1_20160321_054700<br> HGSM3B_0+1_20160306_055900<br> HGSM3B_0+1_20160308_055700<br> HGSM3B_0+1_20160309_055600<br> HGSM3B_0+1_20160316_055100<br> HGSM3B_0+1_20160311_055500<br> HGSM3B_0+1_20160304_060000<br> HGSM3B_0+1_20160322_054600
description: We thank the Management Office of Bawangling National Nature Reserve for logistical assistance in the field. Fieldwork was funded by an Arcus Foundation grant to STT and a Wildlife Acoustics grant to JVB. ID is supported in part by funding from the National Research Foundation of South Africa (Grant ID 90782, 105782). ED is supported by a postdoctoral fellowship from the African Institute for Mathematical Sciences South Africa, Stellenbosch University and the Next Einstein Initiative. This work was carried out with the aid of a grant from the International Development Research Centre, Ottawa, Canada (www.idrc.ca), and with financial support from the Government of Canada, provided through Global Affairs Canada (GAC; www.international.gc.ca). We also thank the following rangers who contributed to data collection: Guang Wei, Zhong Zhao, Qing Lin, Jinbing Zhang, Zhicheng Zhang, Quanjin Li, Xiaoliang Fu, Zhengchong Zhou, Lubiao Huang, Zhengkun Ye, Zhenghai Zou, Jinqiang Wang, Wentao Han and Zengnan Xie.