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The use of machine learning (ML) based techniques has become increasingly popular in the field of bioacoustics over the last years.
Barking in domestic dogs: context specificity and individual identification
Sophia Yin and Brenda McCowan · 2004
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ImageNet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Learning multiple layers of features from tiny images
Alex Krizhevsky · 2009
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Torchvision the machine-vision package of torch
Sébastien Marcel and Yann Rodriguez · 2010
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Scikit-learn: Machine learning in Python
Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, Jake Vanderplas, Alexandre Passos, David Cournapeau, Matthieu Brucher, Matthieu Perrot, and Édouard Duchesnay · 2011
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The MNIST database of handwritten digit images for machine learning research [best of the web]
Li Deng · 2012
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The PASCAL Visual Object Classes Challenge 2012 (VOC2012) development kit, 2012
Mark Everingham and John Winn · 2012
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2014
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 2015
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XGBoost: A scalable tree boosting system
Tianqi Chen and Carlos Guestrin · 2016
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Deep residual learning for image recognition
Kaiming He, X. Zhang, Shaoqing Ren, and Jian Sun · 2016
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The Watkins marine mammal sound database: An online, freely accessible resource
Laela Sayigh, Mary Ann Daher, Julie Allen, Helen Gordon, Katherine Joyce, Claire Stuhlmann, and Peter Tyack · 2016
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Classifying environmental sounds using image recognition networks
Venkatesh Boddapati, Andrej Petef, Jim Rasmusson, and Lars Lundberg · 2017
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Audio Set: An ontology and human-labeled dataset for audio events
Jort F. Gemmeke, Daniel P. W. Ellis, Dylan Freedman, Aren Jansen, Wade Lawrence, R. Channing Moore, Manoj Plakal, and Marvin Ritter · 2017
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CNN architectures for large-scale audio classification
Shawn Hershey, Sourish Chaudhuri, Daniel P. W. Ellis, Jort F. Gemmeke, Aren Jansen, R. Channing Moore, Manoj Plakal, Devin Platt, Rif A. Saurous, Bryan Seybold, Malcolm Slaney, Ron J. Weiss, and Kevin Wilson · 2017
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PMLB: a large benchmark suite for machine learning evaluation and comparison
Randal S. Olson, W. L. Cava, Patryk Orzechowski, Ryan J. Urbanowicz, and Jason H. Moore · 2017
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An annotated dataset of egyptian fruit bat vocalizations across varying contexts and during vocal ontogeny
Yosef Prat, Mor Taub, Ester Pratt, and Yossi Yovel · 2017
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No classification without representation: Assessing geodiversity issues in open data sets for the developing world
Shreya Shankar, Yoni Halpern, Eric Breck, James Atwood, Jimbo Wilson, and D. Sculley · 2017
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Terrestrial passive acoustic monitoring: Review and perspectives
Larissa Sayuri Moreira Sugai, Thiago Sanna Freire Silva, Jr Ribeiro, José Wagner, and Diego Llusia · 2018
Cited alongside, same era.
GLUE: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman · 2018
Cited alongside, same era.
Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition
P. Warden · 2018
Cited alongside, same era.
mixup: Beyond empirical risk minimization
Hongyi Zhang, Moustapha Cisse, Yann N. Dauphin, and David Lopez-Paz · 2018
Cited alongside, same era.
A deafening silence: a lack of data and reproducibility in published bioacoustics research?
Ed Baker and Sarah Vincent · 2019
Cited alongside, same era.
DeepSqueak: a deep learning-based system for detection and analysis of ultrasonic vocalizations
What will it take to fix benchmarking in natural language understanding?
Samuel R. Bowman and George Dahl · 2021
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An annotated set of audio recordings of Eastern North American birds containing frequency, time, and species information
Lauren M. Chronister, Tessa A. Rhinehart, Aidan Place, and Justin Kitzes · 2021
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Mostafa Dehghani, Yi Tay, Alexey A. Gritsenko, Zhe Zhao, Neil Houlsby, Fernando Diaz, Donald Metzler, and Oriol Vinyals · 2021
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Automated detection of Hainan gibbon calls for passive acoustic monitoring
Emmanuel Dufourq, Ian Durbach, James P. Hansford, Amanda Hoepfner, Heidi Ma, Jessica V. Bryant, Christina S. Stender, Wenyong Li, Zhiwei Liu, Qing Chen, Zhaoli Zhou, and Samuel T. Turvey · 2021
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BirdNET: A deep learning solution for avian diversity monitoring
Stefan Kahl, Connor M. Wood, Maximilian Eibl, and Holger Klinck · 2021
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Kevin R. Coffey, Russell G. Marx, and John F. Neumaier · 2019
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
Cited alongside, same era.
Automated bioacoustics: methods in ecology and conservation and their potential for animal welfare monitoring
Michael P. Mcloughlin, Rebecca Stewart, and Alan G. McElligott · 2019
Cited alongside, same era.
SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
Daniel S. Park, William Chan, Yu Zhang, Chung-Cheng Chiu, Barret Zoph, Ekin D. Cubuk, and Quoc V. Le · 2019
Cited alongside, same era.
SuperGLUE: A stickier benchmark for general-purpose language understanding systems
Alex Wang, Yada Pruksachatkun, Nikita Nangia, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman · 2019
Cited alongside, same era.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
Cited alongside, same era.
Quartznet: Deep automatic speech recognition with 1d time-channel separable convolutions
Samuel Kriman, Stanislav Beliaev, Boris Ginsburg, Jocelyn Huang, Oleksii Kuchaiev, Vitaly Lavrukhin, Ryan Leary, Jason Li, and Yang Zhang · 2020
Cited alongside, same era.
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HumBugDB: a large-scale acoustic mosquito dataset
Ivan Kiskin, Marianne E. Sinka, Adam D. Cobb, Waqas Rafique, Lawrence Wang, Davide Zilli, Benjamin Gutteridge, Theodoros Marinos, Yunpeng Li, Emmanuel Wilson Kaindoa, Gerard F Killeen, Katherine J. Willis, and S. Roberts · 2021
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Deep perceptual embeddings for unlabelled animal sound events
Veronica Morfi, Robert F. Lachlan, and Dan Stowell · 2021
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Few-shot bioacoustic event detection: A new task at the dcase 2021 challenge
Veronica Morfi, Inês Nolasco, Vincent Lostanlen, Shubhr Singh, Ariana Strandburg-Peshkin, Lisa F. Gill, Hanna Pamula, David Benvent, and Dan Stowell · 2021
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AI and the everything in the whole wide world benchmark
Inioluwa Deborah Raji, Emily M. Bender, Amandalynne Paullada, Emily L. Denton, and A. Hanna · 2021
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SUPERB: Speech processing universal performance benchmark
Shu wen Yang, Po-Han Chi, Yung-Sung Chuang, Cheng-I Lai, Kushal Lakhotia, Yist Y. Lin, Andy T. Liu, Jiatong Shi, Xuankai Chang, Guan-Ting Lin, Tzu hsien Huang, Wei-Cheng Tseng, Ko tik Lee, Da-Rong Liu, Zili Huang, Shuyan Dong, Shang-Wen Li, Shinji Watanabe, Abdel rahman Mohamed, and Hung yi Lee · 2021
Later among the works it cites.
Hawaiian islands cetacean and ecosystem assessment survey (hiceas) towed array data
NOAA Pacific Islands Fisheries Science Center · 2022
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Efficiently modeling long sequences with structured state spaces
Albert Gu, Karan Goel, and Christopher Ré · 2022
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Tabular data: Deep learning is not all you need
Ravid Shwartz-Ziv and Amitai Armon · 2022
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Computational bioacoustics with deep learning: a review and roadmap
Dan Stowell · 2022
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Perspectives in machine learning for wildlife conservation
Devis Tuia, Benjamin Kellenberger, Sara Beery, Blair R Costelloe, Silvia Zuffi, Benjamin Risse, Alexander Mathis, Mackenzie Weygandt Mathis, Frank van Langevelde, Tilo Burghardt, Roland Kays, Holger Klinck, Martin Wikelski, Iain D Couzin, Grant van Horn, Margaret C Crofoot, Charles V Stewart, and Tanya Berger-Wolf · 2022
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Hear: Holistic evaluation of audio representations
Joseph Turian, Jordie Shier, Humair Raj Khan, Bhiksha Raj, Björn W. Schuller, Christian J. Steinmetz, Colin Malloy, George Tzanetakis, Gissel Velarde, Kirk McNally, Max Henry, Nicolas Pinto, Camille Noufi, Christian Clough, Dorien Herremans, Eduardo Fonseca, Jesse Engel, Justin Salamon, Philippe Esling, Pranay Manocha, Shinji Watanabe, Zeyu Jin, and Yonatan Bisk · 2022
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TorchAudio: Building blocks for audio and speech processing
Yao-Yuan Yang, Moto Hira, Zhaoheng Ni, Anjali Chourdia, Artyom Astafurov, Caroline Chen, Ching feng Yeh, Christian Puhrsch, David Pollack, Dmitriy Genzel, Donny Greenberg, Edward Z. Yang, Jason Lian, Jay Mahadeokar, Jeff Hwang, Ji Chen, Peter Goldsborough, Prabhat Roy, Sean Narenthiran, Shinji Watanabe, Soumith Chintala, Vincent Quenneville-B’elair, and Yangyang Shi · 2022
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