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- speaker-diarization
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- voice-activity-detection
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- speaker-segmentation
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- speaker-diarization
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- voice-activity-detection
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- speaker-segmentation
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---
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## Dataset Description
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The AMI Meeting Corpus consists of 100 hours of meeting recordings. The recordings use a range of signals
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synchronized to a common timeline. These include close-talking and far-field microphones, individual and
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room-view video cameras, and output from a slide projector and an electronic whiteboard. During the meetings,
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the participants also have unsynchronized pens available to them that record what is written. The meetings
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were recorded in English using three different rooms with different acoustic properties, and include mostly
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non-native speakers.
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**Note**: This dataset has been preprocessed using [diarizers](https://github.com/kamilakesbi/diarizers/tree/main/datasets).
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It makes the dataset compatible with `diarizers` scripts to fine-tune `pyannote` segmentation models.
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