Imagine standing on a street corner in the city. With your eyes closed you can hear and
recognize a succession of sounds: cars passing by, people speaking, their footsteps when …

One of the most amazing functions of the human auditory system is the ability to detect all
kinds of sound events in the environment. With the technologies and hardware advances …

Crowdsourcing is a popular tool for collecting large amounts of annotated data, but the
specific format of the strong labels necessary for sound event detection is not easily …

With the development of multi-modal man-machine interaction, audio signal analysis is
gaining importance in a field traditionally dominated by video. In particular, anomalous …

This paper presents an improved mean teacher (MT) based method for large-scale weakly
labeled semi-supervised sound event detection (SED), by focusing on learning a better …

In sound event detection (SED), the representation ability of deep neural network (DNN)
models must be increased to significantly improve the accuracy or increase the number of …

Recently, convolutional neural networks (CNNs) have been widely used in sound event
detection (SED). However, traditional convolution is deficient in learning time-frequency …

Sound event detection (SED) has gained increasing attention with its wide application in
surveillance, video indexing, etc. Existing models in SED mainly generate frame-level …

Sound event detection is an important facet of audio tagging that aims to identify sounds of
interest and define both the sound category and time boundaries for each sound event in a …

Sound event detection (SED) takes on the task of identifying presence of specific sound
events in a complex audio recording. SED has tremendous implications in video analytics …