English

MeetDot: Videoconferencing with Live Translation Captions

Computation and Language 2021-09-21 v1 Artificial Intelligence

Abstract

We present MeetDot, a videoconferencing system with live translation captions overlaid on screen. The system aims to facilitate conversation between people who speak different languages, thereby reducing communication barriers between multilingual participants. Currently, our system supports speech and captions in 4 languages and combines automatic speech recognition (ASR) and machine translation (MT) in a cascade. We use the re-translation strategy to translate the streamed speech, resulting in caption flicker. Additionally, our system has very strict latency requirements to have acceptable call quality. We implement several features to enhance user experience and reduce their cognitive load, such as smooth scrolling captions and reducing caption flicker. The modular architecture allows us to integrate different ASR and MT services in our backend. Our system provides an integrated evaluation suite to optimize key intrinsic evaluation metrics such as accuracy, latency and erasure. Finally, we present an innovative cross-lingual word-guessing game as an extrinsic evaluation metric to measure end-to-end system performance. We plan to make our system open-source for research purposes.

Keywords

Cite

@article{arxiv.2109.09577,
  title  = {MeetDot: Videoconferencing with Live Translation Captions},
  author = {Arkady Arkhangorodsky and Christopher Chu and Scot Fang and Yiqi Huang and Denglin Jiang and Ajay Nagesh and Boliang Zhang and Kevin Knight},
  journal= {arXiv preprint arXiv:2109.09577},
  year   = {2021}
}

Comments

7 pages, 4 figures, Accepted as EMNLP 2021 demo paper

R2 v1 2026-06-24T06:08:37.581Z