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README.md

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+---
+language:
+- el
+license: cc-by-4.0
+task_categories:
+- text-to-speech
+- automatic-speech-recognition
+pretty_name: TTS-Greek
+size_categories:
+- 10K<n<100K
+tags:
+- audio
+- speech
+- greek
+- tts
+- audiobooks
+---
+
+# TTS-Greek
+
+A large-scale, high-quality Greek speech dataset for text-to-speech and automatic speech recognition.
+
+## Data Sources
+
+This dataset combines two sources:
+
+| Source | Samples | Hours | License | Content |
+|--------|---------|-------|---------|---------|
+| **[LibriVox](https://librivox.org/)** | 34,727 | 96.8 | Public Domain | Modern Greek classic literature, philosophy, fiction |
+| **[FLEURS-R](https://huggingface.co/datasets/google/fleurs-r)** (Google) | 4,124 | 12.6 | CC-BY 4.0 | Wikipedia-sourced sentences, AI-restored audio |
+
+## Dataset Statistics
+
+| Metric | Value |
+|--------|-------|
+| Total samples | 38,851 |
+| Total duration | 109 hours |
+| Unique speakers | 35 |
+| Average duration | 10.1 seconds |
+| Average DNSMOS | 3.90 |
+
+## Gender Distribution
+
+| Gender | Samples | Hours |
+|--------|---------|-------|
+| Male | 15,300 | 44.1 |
+| Female | 23,551 | 65.3 |
+
+## Features
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `__key__` | string | Unique sample identifier |
+| `mp3` | Audio | Audio (24kHz mono WAV) |
+| `text` | string | Transcription |
+| `language` | string | Language code (`el`) |
+| `speaker_id` | string | Speaker/audiobook identifier |
+| `gender` | string | `male` or `female` |
+| `dnsmos` | float | Audio quality score (1-5) |
+
+## Processing Pipeline
+
+Audio was processed through:
+1. Standardization (24kHz mono, -20dBFS normalization)
+2. Voice Activity Detection (Silero VAD)
+3. Transcription & forced alignment (WhisperX)
+4. Segmentation (5-15s segments at natural pauses)
+5. Noise reduction (DeepFilterNet)
+6. Quality filtering (DNSMOS)
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("datadriven-company/TTS-Greek", split="train")
+
+# Access a sample
+sample = ds[0]
+print(sample["text"])
+# Audio: sample["mp3"]
+```
+
+## License
+
+The combined dataset is licensed under **CC-BY 4.0** (the more restrictive of the two source licenses).
+Attribution: LibriVox (Public Domain) + Google FLEURS-R (CC-BY 4.0).

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