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---
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license: cc-by-4.0
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tags:
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- audio-diarization
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- speaker-segmentation
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language:
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- kk
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---
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# Diarizations Dataset
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Aggregated speaker segmentation outputs.
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## Videos
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### `ecx7ywj89m4`
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- Segments: **54**
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- Speakers: **SPEAKER_00, SPEAKER_01**
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- Duration: **2369.59s**
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#### Config
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- Trimmed: none
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- Diarize model: `pyannote/speaker-diarization`
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- ASR model: `akuzdeuov/whisper-base.kk` chunk `30s`, lang `kk`
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- Batch: `16`
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### `FWmr-zrGK_w`
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- Segments: **206**
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- Speakers: **SPEAKER_00, SPEAKER_01, SPEAKER_02**
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- Duration: **3071.74s**
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#### Config
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- Trimmed: none
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- Diarize model: `pyannote/speaker-diarization`
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- ASR model: `akuzdeuov/whisper-base.kk` chunk `30s`, lang `kk`
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- Batch: `16`
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### `FzeUEbA6j4E`
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- Segments: **535**
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- Speakers: **SPEAKER_00, SPEAKER_01, SPEAKER_02, SPEAKER_03**
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- Duration: **4425.93s**
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#### Config
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- Trimmed: none
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- Diarize model: `pyannote/speaker-diarization`
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- ASR model: `akuzdeuov/whisper-base.kk` chunk `30s`, lang `kk`
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- Batch: `16`
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### `WC_8foLpFbE`
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- Segments: **158**
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- Speakers: **SPEAKER_00, SPEAKER_01, SPEAKER_02**
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- Duration: **3605.37s**
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#### Config
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- Trimmed: none
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- Diarize model: `pyannote/speaker-diarization`
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- ASR model: `akuzdeuov/whisper-base.kk` chunk `30s`, lang `kk`
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- Batch: `16`
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## Usage
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```python
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from datasets import load_dataset
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ds = load_dataset('pushthetempo/diarizations')
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print(ds)
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``` |
