Audio-language models (ALMs) generate linguistic descriptions of sound-producing events
and scenes. Advances in dataset creation and computational power have led to significant …

Latent diffusion models have shown promising results in text-to-audio (T2A) generation
tasks, yet previous models have encountered difficulties in generation quality, computational …

Despite significant advancements in neural text-to-audio generation, challenges persist in
controllability and evaluation. This paper addresses these issues through the Sound Scene …

We introduce TangoFlux, an efficient Text-to-Audio (TTA) generative model with 515M
parameters, capable of generating up to 30 seconds of 44.1 kHz audio in just 3.7 seconds …

Recent years have seen significant progress in Text-To-Audio (TTA) synthesis, enabling
users to enrich their creative workflows with synthetic audio generated from natural …

In this paper, we introduce SoloAudio, a novel diffusion-based generative model for target
sound extraction (TSE). Our approach trains latent diffusion models on audio, replacing the …

This paper presents Task 7 at the DCASE 2024 Challenge: sound scene synthesis. Recent
advances in sound synthesis and generative models have enabled the creation of realistic …

Fugatto is a versatile audio synthesis and transformation model capable of following free-
form text instructions with optional audio inputs. While large language models (LLMs) …

With the success of large language models (LLMs) driving progress towards general-
purpose AI, there has been a growing focus on extending these models to multi-modal …