README.md

---
dataset_info:
  features:
  - name: transcription
    dtype: string
  - name: start
    dtype: float64
  - name: end
    dtype: float64
  - name: duration
    dtype: float64
  - name: word_count
    dtype: int64
  - name: source_file
    dtype: string
  - name: audio_quality
    struct:
    - name: rms_energy
      dtype: float64
    - name: silence_ratio
      dtype: float64
  - name: vad_refinement
    struct:
    - name: ctc_end
      dtype: float64
    - name: ctc_start
      dtype: float64
    - name: enabled
      dtype: bool
    - name: end_adjustment
      dtype: float64
    - name: search_windows
      sequence: float64
    - name: start_adjustment
      dtype: float64
    - name: vad_end
      dtype: float64
    - name: vad_start
      dtype: float64
  - name: speaker_validation
    struct:
    - name: has_overlap
      dtype: bool
    - name: is_valid
      dtype: bool
    - name: overlap_duration
      dtype: float64
    - name: rejection_reason
      dtype: 'null'
    - name: segments
      list:
      - name: end
        dtype: float64
      - name: speaker
        dtype: string
      - name: start
        dtype: float64
    - name: speaker_count
      dtype: int64
  - name: audio
    dtype: audio
  splits:
  - name: train
    num_bytes: 214388341262.102
    num_examples: 1292013
  download_size: 208980676541
  dataset_size: 214388341262.102
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# TTS Audio Dataset

### Description
Uzbek audio dataset for STT and TTS tasks.  
All audio is cleaned and split into short chunks.  
Each chunk has a transcription with word-level timestamps.

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### Data Format
- **Audio:** FLAC, 24 kHz, 16-bit PCM  
- **Text:** Transcriptions with timestamps (UTF-8)

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### Source
Collected from publicly available materials.

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### Processing Notes
Audio is denoised and chunked.
Text is aligned at the word level for training.

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### Use Cases
Ready for training speech-to-text and text-to-speech models.