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This work focuses on reliable detection of bird sound emissions as recorded in the open field. Acoustic detection of avian sounds can be used for the automatized monitoring of multiple bird taxa and querying in long-term recordings for…

Sound · Computer Science 2016-09-28 Ilyas Potamitis

Biodiversity monitoring using audio recordings is achievable at a truly global scale via large-scale deployment of inexpensive, unattended recording stations or by large-scale crowdsourcing using recording and species recognition on mobile…

Machine Learning · Statistics 2015-05-26 Timos Papadopoulos , Stephen Roberts , Kathy Willis

Many animals emit vocal sounds which, independently from the sounds' function, embed some individually-distinctive signature. Thus the automatic recognition of individuals by sound is a potentially powerful tool for zoology and ecology…

Sound · Computer Science 2018-10-23 Dan Stowell , Tereza Petrusková , Martin Šálek , Pavel Linhart

Autonomous recording units and passive acoustic monitoring present minimally intrusive methods of collecting bioacoustics data. Combining this data with species agnostic bird activity detection systems enables the monitoring of activity…

Audio and Speech Processing · Electrical Eng. & Systems 2022-10-04 Mark Anderson , Naomi Harte

Bioacoustic sensors, sometimes known as autonomous recording units (ARUs), can record sounds of wildlife over long periods of time in scalable and minimally invasive ways. Deriving per-species abundance estimates from these sensors requires…

For centuries researchers have used sound to monitor and study wildlife. Traditionally, conservationists have identified species by ear; however, it is now common to deploy audio recording technology to monitor animal and ecosystem sounds.…

Sound · Computer Science 2021-03-15 C. Chalmers , P. Fergus , S. Wich , S. N. Longmore

Automatic detection and classification of animal sounds has many applications in biodiversity monitoring and animal behaviour. In the past twenty years, the volume of digitised wildlife sound available has massively increased, and automatic…

Prior work in computational bioacoustics has mostly focused on the detection of animal presence in a particular habitat. However, animal sounds contain much richer information than mere presence; among others, they encapsulate the…

Insects are an integral part of our ecosystem. These often small and evasive animals have a big impact on their surroundings, providing a large part of the present biodiversity and pollination duties, forming the foundation of the food…

Sound · Computer Science 2022-11-18 Marius Faiß

Monitoring of bird populations has played a vital role in conservation efforts and in understanding biodiversity loss. The automation of this process has been facilitated by both sensing technologies, such as passive acoustic monitoring,…

Machine Learning · Computer Science 2021-08-23 Irina Tolkova , Brian Chu , Marcel Hedman , Stefan Kahl , Holger Klinck

Acoustic event detection and scene classification are major research tasks in environmental sound analysis, and many methods based on neural networks have been proposed. Conventional methods have addressed these tasks separately; however,…

Insect population numbers and biodiversity have been rapidly declining with time, and monitoring these trends has become increasingly important for conservation measures to be effectively implemented. But monitoring methods are often…

Sound · Computer Science 2024-02-01 Marius Faiß , Dan Stowell

Ecological and conservation studies monitoring bird communities typically rely on species classification based on bird vocalizations. Historically, this has been based on expert volunteers going into the field and making lists of the bird…

Methodology · Statistics 2026-05-29 Haoxuan Wang , Patrik Lauha , David B. Dunson

Assessing the presence and abundance of birds is important for monitoring specific species as well as overall ecosystem health. Many birds are most readily detected by their sounds, and thus passive acoustic monitoring is highly…

Sound · Computer Science 2024-02-01 Dan Stowell , Yannis Stylianou , Mike Wood , Hanna Pamuła , Hervé Glotin

We present a robust classification approach for avian vocalization in complex and diverse soundscapes, achieving second place in the BirdCLEF2021 challenge. We illustrate how to make full use of pre-trained convolutional neural networks, by…

Sound · Computer Science 2021-07-19 Christof Henkel , Pascal Pfeiffer , Philipp Singer

Animal vocalisations and natural soundscapes are fascinating objects of study, and contain valuable evidence about animal behaviours, populations and ecosystems. They are studied in bioacoustics and ecoacoustics, with signal processing and…

Sound · Computer Science 2024-02-01 Dan Stowell

Analyses for biodiversity monitoring based on passive acoustic monitoring (PAM) recordings is time-consuming and challenged by the presence of background noise in recordings. Existing models for sound event detection (SED) worked only on…

Biodiversity loss poses a significant threat to humanity, making wildlife monitoring essential for assessing ecosystem health. Avian species are ideal subjects for this due to their popularity and the ease of identifying them through their…

Machine Learning · Computer Science 2026-02-23 Nina Brolich , Simon Geis , Maximilian Kasper , Alexander Barnhill , Axel Plinge , Dominik Seuß

This paper presents a context-aware framework for feature selection and classification procedures to realize a fast and accurate audio event annotation and classification. The context-aware design starts with exploring feature extraction…

Sound · Computer Science 2023-03-08 M. Mehrdad Morsali , Hoda Mohammadzade , Saeed Bagheri Shouraki

Devices capable of detecting and categorizing acoustic scenes have numerous applications such as providing context-aware user experiences. In this paper, we address the task of characterizing acoustic scenes in a workplace setting from…

Audio and Speech Processing · Electrical Eng. & Systems 2019-11-12 Arindam Jati , Amrutha Nadarajan , Karel Mundnich , Shrikanth Narayanan
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