Showing eess.ASShow all
3 papers · 1 filter
eess.AS2025
SAM Audio: Segment Anything in Audio
Bowen Shi, Andros Tjandra, John Hoffman +11
General audio source separation is a key capability for multimodal AI systems that can perceive and reason about sound. Despite substantial progress in recent years, existing separ…
eess.AS2025
Audiobox TTA-RAG: Improving Zero-Shot and Few-Shot Text-To-Audio with Retrieval-Augmented Generation
Mu Yang, Bowen Shi, Matthew Le +2
This work focuses on improving Text-To-Audio (TTA) generation on zero-shot and few-shot settings (i.e. generating unseen or uncommon audio events). Inspired by the success of Retri…
eess.AS2024
Learning Fine-Grained Controllability on Speech Generation via Efficient Fine-Tuning
Chung-Ming Chien, Andros Tjandra, Apoorv Vyas +3
As the scale of generative models continues to grow, efficient reuse and adaptation of pre-trained models have become crucial considerations. In this work, we propose Voicebox Adap…