Animal vocalisations and natural soundscapes are fascinating objects of study, and contain
valuable evidence about animal behaviours, populations and ecosystems. They are studied …

Acoustic scene classification (ASC) has gained significant interest recently due to its diverse
applications. Various audio signal processing and machine learning methods have been …

The advancement of audio-language (AL) multimodal learning tasks has been significant in
recent years, yet the limited size of existing audio-language datasets poses challenges for …

Audio classification is an important task of map** audio samples into their corresponding
labels. Recently, the transformer model with self-attention mechanisms has been adopted in …

This report introduces FunAudioLLM, a model family designed to enhance natural voice
interactions between humans and large language models (LLMs). At its core are two …

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 …

The recent success of the generative model shows that leveraging the multi-modal
embedding space can manipulate an image using text information. However, manipulating …

Automated audio captioning is a cross-modal translation task that aims to generate natural
language descriptions for given audio clips. This task has received increasing attention with …

The acoustic emission (AE) technique is one of the most widely used in the field of structural
monitoring. Its popularity mainly stems from the fact that it belongs to the category of non …

With the development of machine learning techniques, the attention of research has been
moved from single-modal learning to multi-modal learning, as real-world data exist in the …