101 citations · 107 across the 2 of their papers we have counts for
6 papers
SimulEval: An Evaluation Toolkit for Simultaneous Translation
Xutai Ma, Mohammad Javad Dousti, Changhan Wang +2
Simultaneous translation on both text and speech focuses on a real-time and low-latency scenario where the model starts translating before reading the complete source input. Evalua…
CoVoST: A Diverse Multilingual Speech-To-Text Translation Corpus
Changhan Wang, Juan Pino, Anne Wu +1
Spoken language translation has recently witnessed a resurgence in popularity, thanks to the development of end-to-end models and the creation of new corpora, such as Augmented Lib…
VizSeq: A Visual Analysis Toolkit for Text Generation Tasks
Changhan Wang, Anirudh Jain, Danlu Chen +1
Automatic evaluation of text generation tasks (e.g. machine translation, text summarization, image captioning and video description) usually relies heavily on task-specific metrics…
Neural Machine Translation with Byte-Level Subwords
Changhan Wang, Kyunghyun Cho, Jiatao Gu
Almost all existing machine translation models are built on top of character-based vocabularies: characters, subwords or words. Rare characters from noisy text or character-rich la…
Does Object Recognition Work for Everyone?
Terrance DeVries, Ishan Misra, Changhan Wang +1
The paper analyzes the accuracy of publicly available object-recognition systems on a geographically diverse dataset. This dataset contains household items and was designed to have…
Levenshtein Transformer
Jiatao Gu, Changhan Wang, Jake Zhao
Modern neural sequence generation models are built to either generate tokens step-by-step from scratch or (iteratively) modify a sequence of tokens bounded by a fixed length. In th…