3.7k citations
- Meta (United States)US158 papers
- New York UniversityUS11 papers
- Carnegie Mellon UniversityUS10 papers
- University of California, BerkeleyUS8 papers
- Stanford UniversityUS7 papers
- University of WashingtonUS7 papers
- Cornell UniversityUS6 papers
- University of OxfordGB6 papers
- Massachusetts Institute of TechnologyUS5 papers
- Meta (Israel)IL5 papers
- ETH ZurichCH4 papers
- Google (United States)US4 papers
67 papers · 1 filter
Libri-Light: A Benchmark for ASR with Limited or No Supervision
Jacob Kahn, Morgane Rivière, Weiyi Zheng +12
We introduce a new collection of spoken English audio suitable for training speech recognition systems under limited or no supervision. It is derived from open-source audio books f…
Statistical Testing on ASR Performance via Blockwise Bootstrap
Zhe Liu, Fuchun Peng
A common question being raised in automatic speech recognition (ASR) evaluations is how reliable is an observed word error rate (WER) improvement comparing two ASR systems, where s…
Listen to Look: Action Recognition by Previewing Audio
Ruohan Gao, Tae-Hyun Oh, Kristen Grauman +1
In the face of the video data deluge, today's expensive clip-level classifiers are increasingly impractical. We propose a framework for efficient action recognition in untrimmed vi…
Simplified Action Decoder for Deep Multi-Agent Reinforcement Learning
Hengyuan Hu, Jakob N Foerster
In recent years we have seen fast progress on a number of benchmark problems in AI, with modern methods achieving near or super human performance in Go, Poker and Dota. One common…
Self-Supervised Learning by Cross-Modal Audio-Video Clustering
Humam Alwassel, Dhruv Mahajan, Bruno Korbar +3
Visual and audio modalities are highly correlated, yet they contain different information. Their strong correlation makes it possible to predict the semantics of one from the other…
Fine-grained Synthesis of Unrestricted Adversarial Examples
Omid Poursaeed, Tianxing Jiang, Yordanos Goshu +3
We propose a novel approach for generating unrestricted adversarial examples by manipulating fine-grained aspects of image generation. Unlike existing unrestricted attacks that typ…