activity
20232025
most citedMovie Gen: A Cast of Media Foundation Models

8 citations · 14 across the 9 of their papers we have counts for

collaborators

9 papers

cs.SD2025

Pushing the Frontier of Audiovisual Perception with Large-Scale Multimodal Correspondence Learning

Apoorv Vyas, Heng-Jui Chang, Cheng-Fu Yang +9

We introduce Perception Encoder Audiovisual, PE-AV, a new family of encoders for audio and video understanding trained with scaled contrastive learning. Built on PE, PE-AV makes se…

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…

cs.SD2025★ 1 cited

Meta Audiobox Aesthetics: Unified Automatic Quality Assessment for Speech, Music, and Sound

Andros Tjandra, Yi-Chiao Wu, Baishan Guo +10

The quantification of audio aesthetics remains a complex challenge in audio processing, primarily due to its subjective nature, which is influenced by human perception and cultural…

eess.AS2024

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…

cs.SD2024

MusicFlow: Cascaded Flow Matching for Text Guided Music Generation

K R Prajwal, Bowen Shi, Matthew Lee +8

We introduce MusicFlow, a cascaded text-to-music generation model based on flow matching. Based on self-supervised representations to bridge between text descriptions and music aud…

cs.CV2024★ 8 cited

Movie Gen: A Cast of Media Foundation Models

Adam Polyak, Amit Zohar, Andrew Brown +85

We present Movie Gen, a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio. We also show additional capabili…

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…

cs.SD2023★ 5 cited

Audiobox: Unified Audio Generation with Natural Language Prompts

Apoorv Vyas, Bowen Shi, Matthew Le +21

Audio is an essential part of our life, but creating it often requires expertise and is time-consuming. Research communities have made great progress over the past year advancing t…

eess.AS2023

Generative Pre-training for Speech with Flow Matching

Alexander H. Liu, Matt Le, Apoorv Vyas +3

Generative models have gained more and more attention in recent years for their remarkable success in tasks that required estimating and sampling data distribution to generate high…