---
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)
```