Speech ML Data | On demand Hours of Text-To-Speech (Hard-to-Source Languages) | GDPR, CCPA Compliant | Native Speakers 180+ Countries
Overview
Speech ML Data | On demand Hours of Text-To-Speech (Hard-to-Source Languages) | GDPR, CCPA Compliant | Native Speakers 180+ Countries is an audio and text dataset. Typical applications include speech recognition, speech synthesis (TTS) and robotics & embodied AI. Relevant sectors: AI & Machine Learning, Education and Manufacturing & Industrial. The listing mentions transcription. Pricing is not published and is provided on request.
Primary applications
What the listing offers
- Listing mentions transcription.
Clean, high-quality scripted recordings aligned with transcripts, built for training expressive and natural-sounding TTS systems. Covers a wide range of accents and speaking styles. Available on demand with custom control over speaker accents, environments, metadata, and recording conditions. Scope: Scripted, phonetically balanced recordings with transcripts, optimized for synthetic voice training. Audio Specs: • Sample rate: 48 kHz (studio quality) or 16 kHz for telephony • Scripted prompts across broad phonetic coverage • Configurable voice styles (neutral, expressive, emotional) Volume: hundreds of hours across voices. Speakers: Native speakers in rare and regional languages (Cypriot Greek, Nigerian English, Quebec French, Argentinian Spanish, etc). Transcripts: Aligned text–audio pairs, phonetically balanced. Why Us: • Focus on underserved languages where TTS is missing • On-demand, fast delivery with speaker/environment flexibility • Discounted streaming options for long-term TTS development Use Cases: • Training neural TTS systems • Building synthetic voices for underserved markets • Accent and prosody modeling for global AI assistants
Related datasets
More in Video & Physical AI →Speech ML Data | OTS 5000+ Hours of Free Speech Swahili | GDPR, CCPA Compliant | Native Speakers and Proprietary Data
Clean, high-quality scripted recordings aligned with transcripts, built for training expressive and natural-sounding TTS systems.
- Language
- Swahili
- Volume
- 5,000 h
- Domain
- AI & Machine Learning +2
- Use case
- Speech recognition
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