activity
20242026
collaborators

7 papers

cs.SD2026

Mix2Morph: Learning Sound Morphing from Noisy Mixes

Annie Chu, Hugo Flores García, Oriol Nieto +3

We introduce Mix2Morph, a text-to-audio diffusion model fine-tuned to perform sound morphing without a dedicated dataset of morphs. By finetuning on noisy surrogate mixes at higher…

cs.SD2025

PromptSep: Generative Audio Separation via Multimodal Prompting

Yutong Wen, Ke Chen, Prem Seetharaman +7

Recent breakthroughs in language-queried audio source separation (LASS) have shown that generative models can achieve higher separation audio quality than traditional masking-based…

cs.SD2025

FLAM: Frame-Wise Language-Audio Modeling

Yusong Wu, Christos Tsirigotis, Ke Chen +5

Recent multi-modal audio-language models (ALMs) excel at text-audio retrieval but struggle with frame-wise audio understanding. Prior works use temporal-aware labels or unsupervise…

cs.SD2024

SILA: Signal-to-Language Augmentation for Enhanced Control in Text-to-Audio Generation

Sonal Kumar, Prem Seetharaman, Justin Salamon +2

The field of text-to-audio generation has seen significant advancements, and yet the ability to finely control the acoustic characteristics of generated audio remains under-explore…

cs.SD2024

Sketch2Sound: Controllable Audio Generation via Time-Varying Signals and Sonic Imitations

Hugo Flores García, Oriol Nieto, Justin Salamon +2

We present Sketch2Sound, a generative audio model capable of creating high-quality sounds from a set of interpretable time-varying control signals: loudness, brightness, and pitch,…

cs.CV2024

Video-Guided Foley Sound Generation with Multimodal Controls

Ziyang Chen, Prem Seetharaman, Bryan Russell +4

Generating sound effects for videos often requires creating artistic sound effects that diverge significantly from real-life sources and flexible control in the sound design. To ad…