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🎙️ Telugu Technical Custom Voice Dataset
A high-quality, single-speaker Telugu tech speech dataset designed for fine-tuning text-to-speech (TTS) models like IndicF5-TTS, F5-TTS, XTTS v2, VITS, and ElevenLabs Voice Cloning.
📊 Dataset Overview
- Total Clips: 676 WAV files
- Total Audio Duration: 70.61 minutes (1.18 hours / 4,236.54 seconds)
- Total Disk Size: 1.14 GB
- Average Clip Duration: 6.26 seconds (ranging 2.0s – 15.0s, optimal for TTS attention alignment)
- Audio Format: 22,050 Hz / 48,000 Hz, 16-bit PCM Mono
- STT Transcription Engine: ElevenLabs Scribe V2 (
scribe_v2) - Train / Validation Split: 658 Train clips / 18 Validation clips
🎬 Video Source Breakdown
| Video Title | WAV Clips | Duration | Disk Size |
|---|---|---|---|
| Are we writing IF ELSE conditions properly ? | 171 clips | 17.80 mins | 293.52 MB |
| Production Backend Systems Part 1 | 163 clips | 15.66 mins | 258.29 MB |
| Excel in software dev without CS degree | 149 clips | 17.68 mins | 291.58 MB |
| Why Netflix uses HTTP3 (Part 1) | 122 clips | 12.13 mins | 200.06 MB |
| How 1 thread handles 1M reqs (Node.js, Redis) | 72 clips | 7.35 mins | 121.18 MB |
| TOTAL DATASET | 676 clips | 70.61 mins | 1.14 GB |
📁 Files Structure
wavs/: Isolated voice clips in.wavformat.metadata.csv: Raw ElevenLabs Scribe V2 transcriptions (|delimited).metadata_clean.csv: Cleaned, NFC-normalized text with Code-Switched technical terms.metadata_telugu.csv: Pure Telugu script phonetic transliterations (,delimited).train.csv: Training split (658 clips).val.csv: Validation split (18 clips).
🚀 Usage with Hugging Face Datasets
from datasets import load_dataset
dataset = load_dataset("Noothi/telugu-tech-custom-voice-v2")
print(dataset)
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