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Saving rainforests is a key to halting adverse climate changes. In this paper, we introduce an innovative solution built on acoustic surveillance and machine learning technologies to help rainforest conservation. In particular, We propose…

In this work, we aim to explore the potential of machine learning methods to the problem of beehive sound recognition. A major contribution of this work is the creation and release of annotations for a selection of beehive recordings. By…

The use of machine learning (ML) based techniques has become increasingly popular in the field of bioacoustics over the last years. Fundamental requirements for the successful application of ML based techniques are curated, agreed upon,…

It is argued based on the results of both numerical modelling and the experiments performed on an artificial substitute of a meadow that the sound emitted by animals living in a dense surrounding such as a meadow or shrubs can be used as a…

Voice signal classification based on human behaviours involves analyzing various aspects of speech patterns and delivery styles. In this study, a real-time dataset collection is performed where participants are instructed to speak twelve…

In this research endeavor, it was hypothesized that the sound produced by animals during their vocalizations can be used as identifiers of the animal breed or species even if they sound the same to unaided human ear. To test this…

In this paper we present a research on identification of audio recording devices from background noise, thus providing a method for forensics. The audio signal is the sum of speech signal and noise signal. Usually, people pay more attention…

In the field of wildlife observation and conservation, approaches involving machine learning on audio recordings are becoming increasingly popular. Unfortunately, available datasets from this field of research are often not optimal learning…

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…

Analysis of respiratory sounds increases its importance every day. Many different methods are available in the analysis, and new techniques are continuing to be developed to further improve these methods. Features are extracted from audio…

Animal vocalizations provide crucial insights for wildlife assessment, particularly in complex environments such as forests, aiding species identification and ecological monitoring. Recent advances in deep learning have enabled automatic…

Humans do not acquire perceptual abilities in the way we train machines. While machine learning algorithms typically operate on large collections of randomly-chosen, explicitly-labeled examples, human acquisition relies more heavily on…

Localizing visual sounds consists on locating the position of objects that emit sound within an image. It is a growing research area with potential applications in monitoring natural and urban environments, such as wildlife migration and…

Many approaches have been used in bird species classification from their sound in order to provide labels for the whole of a recording. However, a more precise classification of each bird vocalization would be of great importance to the use…

Reliable identification of bird species in recorded audio files would be a transformative tool for researchers, conservation biologists, and birders. In recent years, artificial neural networks have greatly improved the detection quality of…

In the last several years the use of neural networks as tools to automate species classification from digital data has increased. This has been due in part to the high classification accuracy of image classification through Convolutional…

Machine Learning systems have achieved outstanding performance in different domains. In this paper machine learning methods have been applied to classification task to classify music genre. The code shows how to extract features from audio…

Hornbills, an iconic species of Malaysia's biodiversity, face threats from habi-tat loss, poaching, and environmental changes, necessitating accurate and real-time population monitoring that is traditionally challenging and re-source…

Outdoor shooting ranges are subject to noise regulations from local and national authorities. Restrictions found in these regulations may include limits on times of activities, the overall number of noise events, as well as limits on number…

We introduce machine unlearning for speech tasks, a novel and underexplored research problem that aims to efficiently and effectively remove the influence of specific data from trained speech models without full retraining. This has…