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- ---
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- dataset_info:
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- features:
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- - name: audio_id
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- dtype: string
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- - name: speaker
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- dtype: string
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- - name: start_seconds
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- dtype: float32
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- - name: end_seconds
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- dtype: float32
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- - name: start_ts
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- dtype: string
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- - name: end_ts
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- dtype: string
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- - name: transcript
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- dtype: string
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- - name: overlap
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- dtype: bool
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- - name: audio
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- dtype:
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- audio:
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- sampling_rate: 16000
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- splits:
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- - name: train
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- num_bytes: 431722063.0
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- num_examples: 953
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- download_size: 429777923
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- dataset_size: 431722063.0
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- configs:
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- - config_name: default
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- data_files:
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- - split: train
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- path: data/train-*
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+
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+ # Diarizations Dataset
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+
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+ Aggregated speaker segmentation outputs.
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+
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+ ## Videos
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+
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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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+
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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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+
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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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+
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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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+
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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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+ ```