Automatic large-scale classification of bird sounds is strongly improved by unsupervised feature learning

Cited by (294)

Items 201–294 of 294

1. Group chorusing as an intragroup signal in the greater ani, a communally breeding bird
   Amanda G. Savagian, Christina Riehl · 2022 · Ethology
2. Empirical Evaluation of Variational Autoencoders and Denoising Diffusion Models for Data Augmentation in Bioacoustics Classification
   Charles Herbst, Lorène Jeantet, Emmanuel Dufourq · 2024 · Communications in computer and information science
3. Classifying Bird Songs Based on Chroma and Spectrogram Feature Extraction
   Sara A. Shehab, Ashraf Darwish, Aboul Ella Hassanien · 2024 · Studies in systems, decision and control
4. Dictionary extraction from a collection of spectrograms for bioacoustics monitoring
   José Francisco Ruiz-Muñoz, Zeyu You, Raviv Raich, Xiaoli Z. Fern · 2015 · Machine learning for signal processing ...
5. Deductive refinement of species labelling in weakly labelled birdsong recordings
   Veronica Morfi, Dan Stowell · 2017 · IEEE International Conference on Acoustics Speech and Signal Processing
6. A Generalized Denoising Method with an Optimized Loss Function for Automated Bird Sound Recognition
   Huangqiang Fang, Yulin He, Wanyang Xu, Yanyan Xu, Dengfeng Ke, Kaile Su · 2020 · International Conference on Computer and Communication Systems (ICCCS)
7. Construction of a Data Integration Platform for the Passive Monitoring of the Antillean Manatee in Panama
   Kenji Contreras, Fernando Merchán, Héctor Poveda, Héctor M. Guzmán, Javier E. Sánchez-Galán · 2023 · IEEE Latin-American Conference on Communications
8. Exploring the potential of combining Mel spectrograms with neural networks optimized by the modified crayfish optimization algorithm for acoustic speed violation identification
   Marko Stankovic, Luka Jovanović, Aleksandra Bozovic, Nebojša Budimirović, Miodrag Z. Zivkovic, Nebojša Bačanin · 2024 · International Journal of Hybrid Intelligent Systems
9. Identification of Bird Species Through Audio Signal Processing Using Neural Network
   Singh Ajeet Kumar, Manish Verma, Vishal Kumar, Golu Kumar · 2024 · Lecture notes in networks and systems
10. Evaluation of acoustic pattern recognition of nightingale (Luscinia megarhynchos) recordings by citizens
    Marcel Stehle, Mario Lasseck, Omid Khorramshahi, Ulrike Sturm · 2020 · Research Ideas and Outcomes
11. Using Neural Networks to Identify Bird Species from Birdsong Samples
    Russell Houpt, Mark Pearson, Paul Thomas Pearson, Taylor Rink, Sarah Seckler, Darin R. Stephenson, Alli VanderStoep · 2020 · Foundations for undergraduate research in mathematics
12. BirdCLEF 2015 Submission: Unsupervised Feature Learning from Audio.
    Dan Stowell · 2015 · CLEF (Working Notes)
13. Effect of Revisitation Surveys on Detection of Wetland Birds with Different Diel Vocalization Patterns
    Van T. La, Thomas D. Nudds · 2016 · Journal of Fish and Wildlife Management
14. Noninvasive Sampling Techniques for Vertebrate Fauna
    Leonardo da Silva Chaves, Christini B. Caselli, Rafael de Albuquerque Carvalho, Rômulo Romeu Nóbrega Alves · 2018 · Springer protocols handbooks/Springer protocols
15. Acoustic index-based models for determining time of day in long duration environmental audio recordings
    James Watkins, James Montgomery · 2020 · Ecological Indicators
16. Nocturnal Migration in the Tataka Area, Yushan National Park, Taiwan in Autumn 2014
    Chao‐Chieh Chen, Jane-Chi Wu, Bruno Andreas Walther, Po-Jen Chiang · 2020 · ORNITHOLOGICAL SCIENCE
17. Revealing structure in vocalisations of parrots and social whales
    Maria Florencia Noriega Romero Vargas · 2018
18. Machine Learning-Based Analysis of Bird Vocalizations
    Burooj Ghani · 2022
19. Research progress of birdsong recognition algorithms based on machine learning
    Xiaohu Shen, Xiangyu Zhu, Hongfei Shi, Chuanzhi Wang · 2023 · Biodiversity Science
20. Challenges and Limitations of AI in Wildlife Conservation
    Uma Shekhawat, Udham Singh Rana, Neenu Saini · 2025 · Advances in environmental engineering and green technologies book series
21. Convolutional Neural Networks for audio classification on ultra low power IoT devices
    Alessandro Andreadis, Giovanni Giambene, Riccardo Zambon · 2021 · IEEE International Black Sea Conference on Communications and Networking
22. Deployment of Bird-Vocal Recognition System Using Deep Automatics Artificial Intelligence
    Ajay Kumar, Debolina Ghosh, Vivek Kumar, Jagannath Singh · 2025 · Lecture notes in networks and systems
23. An Initial Study on Birdsong Re-synthesis Using Neural Vocoders
    Rhythm Bhatia, Tomi Kinnunen · 2022 · Lecture notes in computer science
24. Soundscape composition: hearing the real and surreal
    Pablo Rubio Vargas, Jorge Rodrigo Sigal Sefchovich · 2023 · Revista Música
25. Transfer Learning for Generalized Audio Signal Processing
    Stavros Ntalampiras · 2021 · Springer eBooks
26. Virtual birding : extending birdwatching to review acoustic recordings
    Mark Cottman-Fields · 2017 · Queensland University of Technology
27. Smart Sampling of Environmental Audio Recordings for Biodiversity Monitoring
    Philip Eichinski · 2018 · Queensland University of Technology
28. The Contribution of Private Forestland Management and Monitoring to Avian Conservation in Pine Systems in South Carolina
    Jesse M. Wood · 2018 · TigerPrints (Clemson University)
29. End-To-End Auditory Object Recognition Via Inception Nucleus
    Mohammad Kazem Ebrahimpour, Andreea Danielescu, Timothy M. Shea, David C. Noelle, Christopher T. Kello · 2020 · arXiv (Cornell University)
30. Quantitative Modelling of Climate Change Impact on Hydro-climatic Extremes
    Han Wang · 2021
31. On-Edge Device Optimization Using Multiple Classification Method for a Cat and Dog Audio Classifier
    Wicaksono Leksono Muhamad, Dwi Ahmad Dzulhijjah, Fathin Difa Robbani, Dyah Aruming Tyas · 2025 · International Conference on Advancement in Data Science, E-learning and Information System (ICADEIS)
32. Improving one-dimensional-based environmental sound classification models with progressive projection knowledge distillation from two-dimensional-based models
    Huaxing Xu, Haoyuan Chen, Xudong Liu, Haichuan Ren · 2025 · Engineering Applications of Artificial Intelligence
33. Traditional bioacoustic analyses and machine-learning methods indicate weak vocal dimorphism in four Cerrado antbird species
    Enrico Lopes Breviglieri, Larissa Sayuri Moreira Sugai, Guilherme Sementili Cardoso, Reginaldo José Donatelli, Irina Tolkova · 2026 · Journal für Ornithologie
34. Unsupervised classification of graded animal vocalisations using fuzzy clustering
    Benjamin Benti, Patrick JO Miller, Heike Vester, Florencia Noriega, Charlotte Curé · 2025 · Bioacoustics
35. Contrastive learning for passive acoustic monitoring: A framework for sound source discovery and cross-site comparison in marine soundscapes
    Richard Acs, Ali Ibrahim, Hanqi Zhuang, Laurent Marcel Chérubin · 2026 · PLoS Computational Biology
36. Investigating the structure of the greylag goose vocal repertoire: what can unsupervised methods tell us?
    Lena Gies, Jonas Lesigang, Sonia Kleindorfer, Tecumseh Fitch · 2026 · Scientific Reports
37. Visual Analytics of Eco-Acoustic Recordings: The Use of Acoustic Indices to Visualise 24-Hour Recordings
    Mangalam Sankupellay, Tshering Dema, Sandhya Tarar, Michael Towsey, Anthony Truskinger, Margot F. Brereton, Paul Roe · 2016 · Big Data Visual and Immersive Analytics
38. An overview of practices used in environmental sound classification
    Miroslav Chochul, P. Sevcik · 2021 · International Conference on Emerging eLearning Technologies and Applications (ICETA)
39. Improved Bird Sound Classification Based on Deep Cascade Feature
    Jie Xie, Kai Hu, Mingying Zhu · 2022 · IEEE International Conference on Information, Communication and Networks (ICICN)
40. Utilizing Unlabeled Data and Synthetic Data for Bird Sound Detection: Consistency Training, Mean Teacher, and Domain Adaptation Techniques
    Fang-Ching Chen, Yiwen Liu · 2023 · Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)
41. DBS-NET: A Dual-Branch Network Integrating Supervised and Contrastive Self-Supervised Learning for Birdsong Classification
    Ziyi Wang, Hao Shi, Yan Zhang, Yong Cao, Danjv Lv · 2025 · Applied Sciences
42. RNN and Mel-spectrogram based acoustic balancing and bouncing of ping pong ball
    M. Hassan Tanveer, Mark Sabbagh, Antony Thomas, Basit Muhammad Imran, Mumtaz Hussain Soomro · 2020 · International Conference on Computing, Networking, Telecommunications & Engineering Sciences Applications (CoNTESA)
43. AUTOMATIC IDENTIFICATION OF SPECIES FOR ADVANCED AND EFFICIENT RAPTOR SURVEYS: IMPROVING ACCURACY BY NEURAL NETWORKS AND NOISE REDUCTION
    Masamichi YAMAKAWA, Masato Mae, Toshimichi KATAGIRI, Noboru Kanedera, Retsu FUJII, Yusuke Ueno · 2021 · Journal of Japan Society of Civil Engineers Ser G (Environmental Research)
44. Human nonverbal vocalizations
    Andrey Anikin · 2020 · Lund University Publications (Lund University)
45. Applications of artificial intelligence in behavioral finance getting benefit from extended data sources
    Yang Liu · 2020
46. Assessment of animal acoustic diversity in neotropical forest
    Juan Sebastián Ulloa · 2018
47. Listening forward: emerging roles of bioacoustics in ecology, evolution, and conservation
    Zsebők, Sándor · 2026 · Biologia Futura
48. Animal call segregation using self organizing map with speeded up robust features
    Kevin Pelzers, Valeri Mladenov · 2016 · Symposium on Neural Networks and Applications (NEUREL)
49. 136-63: Performance of straight and spiral multipolar coronary sinus leads : preliminary results of the RALLY-X4 study
    Haran Burri, Pascal Defaye, Torsten Kayser, Max Olav Schrage, Giovanni Morani, Stefan Borov, Christophe Leclercq, Mauro Biffi · 2016 · EP Europace
50. Classification and ranking of environmental recordings to facilitate efficient bird surveys
    Liang Zhang · 2017 · Queensland University of Technology
51. Building occupant sensing : occupancy prediction and behavior recognition
    Qingchang Zhu · 2018
52. Feature learning for bird-call segmentation using phase based features
    Rhythm Bhatia, Harshita Seth, Padmanabhan Rajan · 2018 · IEEE International Conference on Industrial and Information Systems (ICIIS)
53. Conv-codes: Audio Hashing For Bird Species Classification
    Anshul Thakur, Pulkit Sharma, Vinayak Abrol, Rajan, Padmanabhan · 2019 · arXiv (Cornell University)
54. 1-D and 2-D convolution neural network for bird sound detection
    Yun Hong Tee · 2020
55. Synaesthetic Sanctuary
    Shaw, William · 2021
56. Mallard Detection Using Microphone Arrays Combined with Delay-and-Sum Beamforming for Smart and Remote Rice–Duck Farming
    Hirokazu Madokoro, Satoshi Yamamoto, Kanji Watanabe, Masayuki Nishiguchi, Stephanie Nix, Hanwool Woo, Kazuhito Sato · 2021 · Applied Sciences
57. Design and Implementation of a Robust Acoustic Recognition System for Waterbird Species Using TMS320C6713 DSK
    Amira Boulmaiz, Djemil Messadeg, Noureddine Doghmane, Abdelmalik Taleb Ahmed · 2020 · IGI Global eBooks
58. Aprendizado de representações com Redes Convolucionais para a identificação de espécies de pássaros e anuros em Paisagens Acústicas
    Fábio Felix Dias · 2022
59. Animal call recognition with acoustic indices and machine learning
    Hongxiao Gan · 2023 · Queensland University of Technology
60. Acoustic Signatures of the Cerrado: Machine Learning Reveals Unique Soundscapes Across Diverse Phytogeographies
    Bruno Daleffi da Silva, Linilson Rodrigues Padovese · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
61. Consistent Birdsong Syllable Segmentation Using Deep Semi-Supervised Learning
    H. Ghaffari, Paul Devos · 2024 · Convention of the European Acoustics Association Forum Acusticum
62. Analyzing long-duration recordings of the environment using autoencoder-extracted features
    Benjamin Rowe · 2024 · Queensland University of Technology
63. Ecologia Acústica e Ciência de Dados: uma análise da paisagem sonora do cerrado Aplicabilidade e desempenho de modelos de aprendizado de máquina na identificação de formações ecológicas.
    Bruno Daleffi da Silva · 2024
64. Danube Delta Bird Sound Recognition
    Svetlana Segărceanu, Maria Niculae, Theodor Pintilie · 2024 · International Conference on Electronics, Computers and Artificial Intelligence (ECAI)
65. A Statistical Feature Extraction Approach using Bird Flight Calls
    K. M. L. K. Mahanayake, Sachith Piyumal Abeysundara · 2025 · International Conference on Advanced Research in Computing (ICARC)
66. Acoustic Signals of House Crow, Corvus splendens splendens Vieillot, LJP 1817 in Agricultural Landscapes of Punjab
    Sakshi Singla, Manoj Kumar · 2024 · Agricultural Research Journal
67. Exploring the Prospect of Hybridizing Mel Spectrograms and Neural Networks for Acoustic Speed Violation Detection
    Marko Stankovic, Luka Jovanović, Aleksandra Bozovic, Nebojša Budimirović, Miodrag Z. Zivkovic, Nebojša Bačanin · 2025 · Lecture notes in networks and systems
68. Automatic Recognition of Pelung and Canary Bird Sounds Using Machine Learning and Signal Enhancement
    Dyah Agustika Kurniawati, Nur Kadarisman, Sumarna Sumarna, Agus Purwanto · 2025 · POSITRON
69. The Synergy of Artificial Intelligence and Animal Communication
    Arun Agrawal, Anuja Manoj Chavan, Swati Nilesh Pawar, Ashvini Arvind Todkar, Deepak Gupta, Deepak Sudhakar Dharrao, Rakhi Arora, Rajeev Kumar Singh · 2025 · Advances in computational intelligence and robotics book series
70. Decoding Birdsong: A Comprehensive Survey of Audio Descriptors for Bird Species Identification
    Shobha Lolge, Saurabh Deshmukh · 2025 · Current research in systematic musicology
71. ECBirdNet: A Lightweight Convolutional Neural Network with Attention Mechanism for Bird Audio Classification
    Fan Ma, Zhen Wang, Longjia Ye, Kunrong Hu · 2025
72. Music Genre Classification
    Dnyaneshwari Shinde, Altaf Osman Mulani · 2025 · International Journal of Advanced Research in Science Communication and Technology
73. CNN Augmented Dimensionality Reduction With Neural Network Ensembles for Low Resource Data Classification
    Mehdi Ashena, Reza Ghaderi · 2025 · IEEE Access
74. BirdSonic: An AI-Powered System for Real-Time Bird Species Detection Using Audio Classification
    Jeevan Bhandary, Spoorthi P. Shetty, Bharath Bhat, Mangala P Shetty, Shashank Shetty · 2025 · IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER)
75. A Review - Music Genre Classification
    Dnyaneshwari Shinde, Dr. A. O. Mulani · 2025 · International Journal of Advanced Research in Science Communication and Technology
76. Classification of Biological Sounds Using Spatial Directivity
    Jurij Prezelj, Luka Čurović, Jure Murovec, Andrej Hvastja · 2025 · Convention of the European Acoustics Association Forum Acusticum
77. Bird Sound Classification Using Two-Channel Markov Transition Field Transformation Images and Convolutional Neural Networks
    Tricia Jonina B. Alcisto, William Caleb Arcena Perez, Angie M. Ceniza-Canillo · 2025 · International Conference on Artificial Intelligence's Future Implementations (ICAIFI)
78. Inovações na Detecção de Ruídos Antropogênicos com Aprendizado de Máquina
    Felipe R. Ahad, Josiel Maimone de Figueiredo, Alvaro S. C. Junior, Allan Gonçalves de Oliveira · 2025
79. Targeted Data Augmentation Framework for Environmental Audio Classification with Difficult Categories
    Rui Hu, Yujun Li, Qing Zhang, Pengcheng Sun, Yuxing Li, Chenyan Wu · 2026 · SSRN Electronic Journal
80. Toward organic ambient intelligences ? : EMMA
    Clément Duhart · 2016
81. Behavioural responses of two cetacean species to natural and anthropogenic sounds
    Benjamin Benti · 2020
82. Développement d’indices écoacoustiques pour caractériser et suivre l’état et le fonctionnement des écosystèmes coralliens
    Simon Élise · 2019
83. Réponses individuelles et populationnelles à la variabilité spatio-temporelle environnementale d'une espèce longévive : le cas du manchot royal, Aptenodytes patagonicus
    Gaël Bardon · 2024
84. Machine Learning–Driven Analysis of Bird Vocalizations for Early Detection of Environmental Disturbances
    2026 · International Research Journal of Modernization in Engineering Technology and Science
85. A Bird Sound Recognition Method Based on Multi-Scale Feature Fusion and Global-Local Progressive Modeling
    Rui Zhang, Han Li · 2026 · International Conference on Electronics Technology and Artificial Intelligence (ETAI)
86. Echoes of Instinct Decoding Bird Behavior Using Deep Learning
    J. Benita, A.K.Anith, P. K. Vivekanandhan, S.Suthikson, T.Abhinav · 2026 · IEEE International Conference on Emerging Computing and Intelligent Technologies (ICoECIT)
87. Decoding the roar: insights into acoustic detection and attenuation of Asiatic lions’ vocal behaviour
    Mohan Ram, Ram Ratan Nala, Jaipal Singh, Tanisha Dagur, Viral Joshi, Lahar S. Jhala · 2026 · Mammalian Biology
88. Two-stage fine-tuning of HuBERT for multi-label bird species recognition in overlapping acoustic environments
    Hailemariam Abebe Endalamaw, C S Yang · 2026 · Natural Computing
89. BioSeg: An open-source software for bioacoustic segmentation, cluster-assisted labeling, and dataset generation
    Gökhan TURAN, Ecir Uğur Küçüksille, Halil Süel · 2026 · SoftwareX
90. An efficient pipeline for the unsupervised segmentation of heterogeneous natural soundscapes
    Thomas Napier, Euijoon Ahn, Slade Allen‐Ankins, Lin Schwarzkopf, Ickjai Lee · 2026 · Ecological Informatics
91. Two decades of machine learning in bioacoustics: a systematic review
    Eduardo Mora-González, Antonio Canepa, José Antonio Barbero Aparicio, Álvar Arnaiz González · 2026 · Applied Intelligence
92. Artificial Intelligence and Machine Learning in Ecoacoustics
    K.S. Umashankar, Babitha, M.B. Rekha · 2026 · Wiley eBooks
93. Bioacoustics Intelligence
    S. B. Nandini, A. Mamatha, G. S. Veena · 2026 · Wiley eBooks
94. Acoustic event detection for spatiotemporal patterns of bird activity in protected areas
    Xiaoqing Xu, Yaling Huang, Xueyao Sun, Chengyun Zhang, Jiale Ling, Shang Yu · 2026 · The Journal of the Acoustical Society of America