659 citations · 792 across the 9 of their papers we have counts for
9 papers
On The Open Prompt Challenge In Conditional Audio Generation
Ernie Chang, Sidd Srinivasan, Mahi Luthra +8
Text-to-audio generation (TTA) produces audio from a text description, learning from pairs of audio samples and hand-annotated text. However, commercializing audio generation is ch…
In-Context Prompt Editing For Conditional Audio Generation
Ernie Chang, Pin-Jie Lin, Yang Li +6
Distributional shift is a central challenge in the deployment of machine learning models as they can be ill-equipped for real-world data. This is particularly evident in text-to-au…
CVPR 2023 Text Guided Video Editing Competition
Jay Zhangjie Wu, Xiuyu Li, Difei Gao +17
Humans watch more than a billion hours of video per day. Most of this video was edited manually, which is a tedious process. However, AI-enabled video-generation and video-editing…
Stack-and-Delay: a new codebook pattern for music generation
Gael Le Lan, Varun Nagaraja, Ernie Chang +5
In language modeling based music generation, a generated waveform is represented by a sequence of hierarchical token stacks that can be decoded either in an auto-regressive manner…
Enhance audio generation controllability through representation similarity regularization
Yangyang Shi, Gael Le Lan, Varun Nagaraja +6
This paper presents an innovative approach to enhance control over audio generation by emphasizing the alignment between audio and text representations during model training. In th…
Exploring the Design Space of Deep Convolutional Neural Networks at Large Scale
Forrest Iandola
In recent years, the research community has discovered that deep neural networks (DNNs) and convolutional neural networks (CNNs) can yield higher accuracy than all previous solutio…