6 datasets found
  1. h

    ami-sdm

    • huggingface.co
    Updated Mar 21, 2024
    + more versions
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    Whisper Distillation (2024). ami-sdm [Dataset]. https://huggingface.co/datasets/distil-whisper/ami-sdm
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 21, 2024
    Dataset authored and provided by
    Whisper Distillation
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The AMI Meeting Corpus consists of 100 hours of meeting recordings. The recordings use a range of signals synchronized to a common timeline. These include close-talking and far-field microphones, individual and room-view video cameras, and output from a slide projector and an electronic whiteboard. During the meetings, the participants also have unsynchronized pens available to them that record what is written. The meetings were recorded in English using three different rooms with different acoustic properties, and include mostly non-native speakers.

  2. h

    ami

    • huggingface.co
    Updated May 2, 2024
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    diarizers-community (2024). ami [Dataset]. https://huggingface.co/datasets/diarizers-community/ami
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 2, 2024
    Dataset authored and provided by
    diarizers-community
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Dataset Card for the AMI dataset for speaker diarization

    The AMI Meeting Corpus consists of 100 hours of meeting recordings. The recordings use a range of signals synchronized to a common timeline. These include close-talking and far-field microphones, individual and room-view video cameras, and output from a slide projector and an electronic whiteboard. During the meetings, the participants also have unsynchronized pens available to them that record what is written. The meetings… See the full description on the dataset page: https://huggingface.co/datasets/diarizers-community/ami.

  3. h

    AMIsum

    • huggingface.co
    Updated Jul 15, 2023
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    Laboratory of Language Technology at Tallinn University of Technology (2023). AMIsum [Dataset]. https://huggingface.co/datasets/TalTechNLP/AMIsum
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 15, 2023
    Dataset authored and provided by
    Laboratory of Language Technology at Tallinn University of Technology
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Dataset Card for "AMIsum"

      Dataset Summary
    

    AMIsum is meeting summaryzation dataset based on the AMI Meeting Corpus (https://groups.inf.ed.ac.uk/ami/corpus/). The dataset utilizes the transcripts as the source data and abstract summaries as the target data.

      Supported Tasks and Leaderboards
    

    More Information Needed

      Languages
    

    English

      Dataset Structure
    
    
    
    
    
      Data Instances
    

    {'transcript': '

  4. h

    ami-disfluency

    • huggingface.co
    Updated Apr 20, 2025
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    Phuoc Hoang Ho (2025). ami-disfluency [Dataset]. https://huggingface.co/datasets/hhoangphuoc/ami-disfluency
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    Dataset updated
    Apr 20, 2025
    Authors
    Phuoc Hoang Ho
    License

    Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
    License information was derived automatically

    Description

    DSFL Dataset - AMI Disfluency Laughter Events

    This dataset contains segmented audio and video clips from AMI Meeting Corpus, which only consisted of disfluencies and laughter events, segmented in both audio and visual modality. This dataset, along with hhoangphuoc/ami-av is created for my research related to Audio-Visual Speech Recognition, which I currently developed at: https://github.com/hhoangphuoc/AVSL For reproducing the work I've done to create this dataset, checkout the… See the full description on the dataset page: https://huggingface.co/datasets/hhoangphuoc/ami-disfluency.

  5. h

    ami-av

    • huggingface.co
    Updated Apr 3, 2025
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    Phuoc Hoang Ho (2025). ami-av [Dataset]. https://huggingface.co/datasets/hhoangphuoc/ami-av
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    Dataset updated
    Apr 3, 2025
    Authors
    Phuoc Hoang Ho
    Description

    Dataset Summary

    This is the processed Audio-Visual Dataset from AMI Meeting Corpus. 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'… See the full description on the dataset page: https://huggingface.co/datasets/hhoangphuoc/ami-av.

  6. h

    ami-dsfl-av

    • huggingface.co
    Updated Apr 20, 2025
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    Phuoc Hoang Ho (2025). ami-dsfl-av [Dataset]. https://huggingface.co/datasets/hhoangphuoc/ami-dsfl-av
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    Dataset updated
    Apr 20, 2025
    Authors
    Phuoc Hoang Ho
    Description

    AMI DisfluencyLaughter Dataset

    This dataset contains segmented audio and video clips which extract from AMI Meeting Corpus. The segmented audio/videos created in this dataset are mainly the disfluencies and laughter events, extracted from original recordings. General information about this dataset:

    Number of recordings: 35,731 Has audio: True Has video: True Has lip video: True

    Dataset({ features: ['id', 'meeting_id', 'speaker_id', 'start_time', 'end_time', 'duration'… See the full description on the dataset page: https://huggingface.co/datasets/hhoangphuoc/ami-dsfl-av.

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Whisper Distillation (2024). ami-sdm [Dataset]. https://huggingface.co/datasets/distil-whisper/ami-sdm

ami-sdm

distil-whisper/ami-sdm

Explore at:
226 scholarly articles cite this dataset (View in Google Scholar)
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Mar 21, 2024
Dataset authored and provided by
Whisper Distillation
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

The AMI Meeting Corpus consists of 100 hours of meeting recordings. The recordings use a range of signals synchronized to a common timeline. These include close-talking and far-field microphones, individual and room-view video cameras, and output from a slide projector and an electronic whiteboard. During the meetings, the participants also have unsynchronized pens available to them that record what is written. The meetings were recorded in English using three different rooms with different acoustic properties, and include mostly non-native speakers.

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