mlsanityData to 7 Oct 2026

Look, Listen and Recognise: Character-Aware Audio-Visual Subtitling

arXiv 2401.12039 ↗First posted 22 Jan 2024cs.CV cs.SD eess.AScited by 8

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Abstract (arXiv)

The goal of this paper is automatic character-aware subtitle generation. Given a video and a minimal amount of metadata, we propose an audio-visual method that generates a full transcript of the dialogue, with precise speech timestamps, and the character speaking identified. The key idea is to first use audio-visual cues to select a set of high-precision audio exemplars for each character, and then use these exemplars to classify all speech segments by speaker identity. Notably, the method does not require face detection or tracking. We evaluate the method over a variety of TV sitcoms, including Seinfeld, Fraiser and Scrubs. We envision this system being useful for the automatic generation of subtitles to improve the accessibility of the vast amount of videos available on modern streaming services. Project page : urlhttps://www.robots.ox.ac.uk/~vgg/research/look-listen-recognise/

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 19 of its 35 references that are in the map. First posted on arXiv 22 Jan 2024.

Builds on

19 of 35 references.

References · 19

  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. 2020ECAPA-TDNN: Emphasized Channel Attention, Propagation and Aggregation in TDNN Based Speaker Verificationcited by 606
  4. 2023WhisperX: Time-Accurate Speech Transcription of Long-Form Audiocited by 320
  5. 2018Deep Audio-Visual Speech Recognitioncited by 318
  6. 2020Self-Supervised Learning of Audio-Visual Objects from Videocited by 186
  7. 2019The VIA Annotation Software for Images, Audio and Videocited by 166
  8. 2019End-to-End Neural Speaker Diarization with Permutation-Free Objectivescited by 86
  9. 2020Spot the conversation: speaker diarisation in the wildcited by 75
  10. 2017Speaker Diarization with LSTMcited by 73
  11. 2020End-to-End Speaker Diarization for an Unknown Number of Speakers with Encoder-Decoder Based Attractorscited by 70
  12. 2018Fully Supervised Speaker Diarizationcited by 46
7 more
  1. 2021AVA-AVD: Audio-Visual Speaker Diarization in the Wildcited by 24
  2. 2019Who said that?: Audio-visual speaker diarisation of real-world meetingscited by 22
  3. 2018From Benedict Cumberbatch to Sherlock Holmes: Character Identification in TV series without a Scriptcited by 20
  4. 2020Self-supervised learning for audio-visual speaker diarizationcited by 14
  5. 2021Automated Video Labelling: Identifying Faces by Corroborative Evidencecited by 9
  6. 2020Look who's not talkingcited by 6
  7. 2022Audio visual character profiles for detecting background characters in entertainment mediacited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 5; 2026: 1.

8 papers.