Production-Ready Uzbek Speech Data
Uzbek Voice Data, Engineered for AI
From native Uzbek podcasts to verified, segmented, multi-speaker datasets. Plug-and-play with HuggingFace, Common Voice, and LJSpeech.
Building Uzbek Speech Models is Hard
Training Uzbek speech models (ASR, TTS, voice cloning) requires thousands of hours of clean, labeled audio — segmented by speaker, tagged by dialect, scored by quality. Manual collection takes months. We automate the entire pipeline and deliver datasets that are plug-and-play with HuggingFace, Common Voice, and LJSpeech.
Clean audio required for production ASR models
Uzbek dialects with distinct acoustic signatures
Human-verified quality for every segment
Our Pipeline
How It Works
From raw audio to production-ready datasets in three stages
Source & Extract
Audio extracted from Talabam.com podcasts — Uzbekistan's premier content platform. Native speakers, real conversations, 10+ dialects.
- Native Uzbek speech
- Multi-speaker content
- 10+ dialect regions
Process & Clean
7-step pipeline: quality analysis, noise removal (Demucs + DeepFilterNet), Whisper transcription, speaker diarization (Pyannote 3.1).
- VAD filtering (≥50% speech)
- Background music removed
- Word-level timestamps
Verify & Export
Human-in-the-loop review for flagged content. Metadata enrichment: emotion, dialect (10 regions), DNSMOS quality scores.
- Human verification
- 5–30s segments
- HuggingFace compatible
Data Source
Powered by Talabam.com
All audio is sourced from Talabam.com — Uzbekistan's premier podcast and video content platform. This gives us authentic, legally-accessible content with proper consent flows.
Native Speech
Real conversations, not scripted readings
Multi-Speaker
2–6 speakers per episode with natural turn-taking
Regional Diversity
Hosts and guests from all 10+ dialect regions
Fresh Content
Hundreds of hours published weekly
Dialect Coverage
10 Uzbek Dialects
Every segment is tagged with dialect metadata — build models that understand regional variations from all corners of Uzbekistan.
Toshkent
Urban standard, widely used in media
Farg'ona
Distinct intonation patterns
Namangan
Mountain region variety
Samarqand
Historical center dialect
Xorazm
Unique vocabulary influences
Qashqadaryo
Transitional features
Buxoro
Classical influences
Andijon
Agricultural region speech
Navoiy
Mining industry variety
Surxondaryo
Border region dialect
Detection via linguistic markers, acoustic fingerprinting, and human verification
Frequently Asked Questions
Everything you need to know about our voice datasets
Ready to Power Your Voice AI?
Browse our collection of 200+ voice datasets or request custom data tailored to your specific needs.