In this paper, we propose a convolutional recurrent neural network for joint sound event
localization and detection (SELD) of multiple overlapping sound events in three-dimensional …

The seen birds twitter, the running cars accompany with noise, etc. These naturally
audiovisual correspondences provide the possibilities to explore and understand the …

Sound event detection (SED) methods are tasked with labeling segments of audio
recordings by the presence of active sound sources. SED is typically posed as a supervised …

This paper presents DCASE 2018 task 4. The task evaluates systems for the large-scale
detection of sound events using weakly labeled data (without time boundaries). The target of …

Each edition of the challenge on Detection and Classification of Acoustic Scenes and Events
(DCASE) contained several tasks involving sound event detection in different setups …

Audio segmentation and sound event detection are crucial topics in machine listening that
aim to detect acoustic classes and their respective boundaries. It is useful for audio-content …

Learning from data in the quaternion domain enables us to exploit internal dependencies of
4D signals and treating them as a single entity. One of the models that perfectly suits with …

Identification of environment sounds plays a key role in security and surveillance aspects. In
this paper, we present a review and recent advances in a sound event recognition (SER) …

Honeybees play a crucial role in the agriculture industry because they pollinate
approximately 75% of all flowering crops. However, every year, the number of honeybees …

In acoustic event detection, the training data size of some acoustic events is often small and
imbalanced. To deal with this, this paper proposes generating the virtual training data …