6 datasets found
  1. h

    ami_summ

    • huggingface.co
    Updated Dec 22, 2023
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    Yuan, Pei-Chieh (2023). ami_summ [Dataset]. https://huggingface.co/datasets/YuanPJ/ami_summ
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 22, 2023
    Authors
    Yuan, Pei-Chieh
    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-ihm-timestamped

    • huggingface.co
    Updated Feb 24, 2024
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    Whisper Distillation (2024). ami-ihm-timestamped [Dataset]. https://huggingface.co/datasets/distil-whisper/ami-ihm-timestamped
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 24, 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.

  3. h

    ami-sdm-timestamped

    • huggingface.co
    Updated Feb 25, 2024
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    Whisper Distillation (2024). ami-sdm-timestamped [Dataset]. https://huggingface.co/datasets/distil-whisper/ami-sdm-timestamped
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 25, 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.

  4. h

    ami

    • huggingface.co
    • opendatalab.com
    Updated Oct 1, 2022
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    University of Edingburgh - Centre For Speech Technology Research (2022). ami [Dataset]. https://huggingface.co/datasets/edinburghcstr/ami
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Oct 1, 2022
    Dataset authored and provided by
    University of Edingburgh - Centre For Speech Technology Research
    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.

  5. h

    ami-sdm

    • huggingface.co
    Updated Mar 21, 2024
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    Whisper Distillation (2024). ami-sdm [Dataset]. https://huggingface.co/datasets/distil-whisper/ami-sdm
    Explore at:
    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.

  6. h

    ami-ihm

    • huggingface.co
    Updated Mar 21, 2024
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    Cite
    Whisper Distillation (2024). ami-ihm [Dataset]. https://huggingface.co/datasets/distil-whisper/ami-ihm
    Explore at:
    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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Click to copy link
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Close
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Yuan, Pei-Chieh (2023). ami_summ [Dataset]. https://huggingface.co/datasets/YuanPJ/ami_summ

ami_summ

YuanPJ/ami_summ

Explore at:
10 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
Dec 22, 2023
Authors
Yuan, Pei-Chieh
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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