OxfordVGG Submission to the EGO4D AV Transcription Challenge
Jaesung Huh Max Bain Andrew Zisserman
This report presents the technical details of our submission on the EGO4D
Audio-Visual (AV) Automatic Speech Recognition Challenge 2023 from the
OxfordVGG team. We present WhisperX, a system for efficient speech
transcription of long-form audio with word-level time alignment, along with two
text normalisers which are publicly available. Our final submission obtained
56.0% of the Word Error Rate (WER) on the challenge test set, ranked 1st on the
leaderboard. All baseline codes and models are available on
https://github.com/m-bain/whisperX.