Large Language Models (LLMs) have seen significant use in domains such as natural
language processing and computer vision. Going beyond text, image and graphics, LLMs …

This survey paper provides a comprehensive overview of the recent advancements and
challenges in applying large language models to the field of audio signal processing. Audio …

Abstract Language models have been successfully used to model natural signals, such as
images, speech, and music. A key component of these models is a high quality neural …

We introduce a state-of-the-art real-time, high-fidelity, audio codec leveraging neural
networks. It consists in a streaming encoder-decoder architecture with quantized latent …

Self-supervised learning (SSL) has recently emerged as a promising paradigm for training
generalisable models on large-scale data in the fields of vision, text, and speech. Although …

Augmenting large language models (LLMs) to understand audio--including non-speech
sounds and non-verbal speech--is critically important for diverse real-world applications of …

Current sound-based practices and systems developed in both academia and industry point
to convergent research trends that bring together the field of sound and music Computing …

The task of the challenge is to develop a voice anonymization system for speech data which
conceals the speaker's voice identity while protecting linguistic content and emotional states …

Language models have been effectively applied to modeling natural signals, such as
images, video, speech, and audio. A crucial component of these models is the codec …

Text-to-music generation (T2M-Gen) faces a major obstacle due to the scarcity of large-scale
publicly available music datasets with natural language captions. To address this, we …