---
task_categories:
- automatic-speech-recognition
language:
- en
tags:
- audio-visual
- paralinguistic
- conversational-speech
size_categories:
- 10K<n<100K
---
## Dataset Summary
This is the processed Audio-Visual Dataset from [AMI Meeting Corpus](https://groups.inf.ed.ac.uk/ami/download/).
The dataset was segmented into sentence-level audio/video segments based on the individual `[meeting_id]-[speaker_id]` transcripts. 
The purpose of this data is for audio-visual speech recognition task (AVSR), particularly for spontaneous conversational speech.

General information about dataset:

Total #segments: 83,438 (including either audio/video or both)
```
Dataset({
    features: ['id', 'meeting_id', 'speaker_id', 'start_time', 'end_time', 'duration', 'transcript', 'audio', 'video', 'has_audio', 'has_video', 'has_lip_video', 'has_transcript'],
    num_rows: 83438
})
```

in which:
- #audio: 80,285 ~ 13GB
- #videos: 78,685 items ~ 5,6GB
- #lip videos: 67,438 items ~ 1.9GB

Additional Remarks: Audio are segmented and resampled to 16kHz, `.wav` format; Videos are resampled to 25fps, in `.mp4` format
  
## Dataset Folder Structure
Each file of the data have the unique `segment_id` in the format: 
```
  [meeting_id]-[speaker_id]-[start_time]-[end_time]-[audio/video/lip_video].(wav/mp4)
```
The original folder structure that used to store this information is followed:
```
ami /
  |_ audio_segments/
      |_ ES2001a-0.00-0.10-audio.wav
      |_ ...
  |_ video_segments /
      |_ original_videos
          |_ ES2001a-0.00-0.10-video.mp4
          |_ ...
      |_ lips
          |_ ES2001a-0.00-0.10-lip_video.mp4
          |_ ...
```

## Create this dataset
To replicate the creation of this dataset, you can download the original [AMI Meeting Corpus](https://groups.inf.ed.ac.uk/ami/download/). 
This dataset processed from all meeting recordings, original video is `"Low-size DivX AVI videos"` option and original audio is `"Individual headsets"` option.

The details steps to preprocess from original AMI corpus can be followed by this guidelines: 
https://github.com/hhoangphuoc/AVSL/blob/main/docs/Preprocess.md