mlsanityData to 7 Oct 2026

OxfordVGG Submission to the EGO4D AV Transcription Challenge

arXiv 2307.09006 ↗First posted 18 Jul 2023cs.SD cs.LG eess.AScited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 9 of its 15 references that are in the map. First posted on arXiv 18 Jul 2023.

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9 of 15 references.

References · 9

  1. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 3,972
  2. 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,853
  3. 2020Conformer: Convolution-augmented Transformer for Speech Recognitioncited by 1,838
  4. 2017AISHELL-1: An Open-Source Mandarin Speech Corpus and A Speech Recognition Baselinecited by 364
  5. 2023WhisperX: Time-Accurate Speech Transcription of Long-Form Audiocited by 320
  6. 2019pyannote.audio: neural building blocks for speaker diarizationcited by 175
  7. 2023Auto-AVSR: Audio-Visual Speech Recognition with Automatic Labelscited by 113
  8. 2019ASR is all you need: cross-modal distillation for lip readingcited by 85
  9. 2021NeMo Inverse Text Normalization: From Development To Productioncited by 28

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