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