The development of Artificial Intelligence Generated Content (AIGC) has been facilitated by
advancements in model algorithms, scalable foundation model architectures, and the …

The growing popularity of generative music models underlines the need for perceptually
relevant, objective music quality metrics. The Frechet Audio Distance (FAD) is commonly …

Automated Audio Captioning (AAC) is the task of generating natural language descriptions
given an audio stream. A typical AAC system requires manually curated training data of …

Existing datasets for audio understanding primarily focus on single-turn interactions (ie
audio captioning, audio question answering) for describing audio in natural language, thus …

Audio-language models (ALMs) process sounds to provide a linguistic description of sound-
producing events and scenes. Recent advances in computing power and dataset creation …

The rapid advancement of foundation models (FMs) across language, image, audio, and
video domains has shown remarkable capabilities in diverse tasks. However, the …

Speech Emotion Recognition (SER) has been traditionally formulated as a classification
task. However, emotions are generally a spectrum whose distribution varies from situation to …

This paper explores whether considering alternative domain-specific embeddings to
calculate the Fr\'echet Audio Distance (FAD) metric can help the FAD to correlate better with …

Large audio-video language models can generate descriptions for both video and audio.
However, they sometimes ignore audio content, producing audio descriptions solely reliant …

Recent singing-voice-synthesis (SVS) methods have achieved remarkable audio quality and
naturalness, yet they lack the capability to control the style attributes of the synthesized …