In this paper, we propose an effective sound event detection (SED) method based on the
audio spectrogram transformer (AST) model, pretrained on the large-scale AudioSet for …

In this technical report, we present our submissions for DCASE 2023 challenge task4a. We
mainly study how to fine-tune patchout fast spectrogram transformer (PaSST) for sound …

Sound event detection (SED) entails identifying the type of sound and estimating its
temporal boundaries from acoustic signals. These events are uniquely characterized by their …

Due to the high variation in the application requirements of sound event detection (SED)
systems, it is not sufficient to evaluate systems only in a single operating mode. Therefore …

The sense of hearing is fundamental to human beings, as it allows them to perceive their
surroundings. However, this simple task of recognizing different sounds in complex …

This paper is a system description of the XiaoRice team submission to the DCASE 2023
Task 4 challenge. In light of the increasing availability of pretrained audio embedding …

In this technical report, we describe our systems for DCASE 2023 Challenge Task4a. Our
systems are mainly based on Frequency Dynamic Convolutional Recurrent Neural Network …

This technical report describes the CP-JKU team's submission for Task 4 Sound Event
Detection with Heterogeneous Training Datasets and Potentially Missing Labels of the …

Sound event detection (SED) is one of tasks to automate function by human auditory system
which listens and understands auditory scenes. Therefore, we were inspired to make SED …

We describe our submitted systems for DCASE2023 Task4 in this technical report: Sound
Event Detection with Weak Labels and Synthetic Soundscapes (Subtask A), and Sound …