RakshaVoice cloning is one of the most exciting and challenging applications of artificial intelligence. From personalised virtual assistants to dubbing in entertainment, the success of any voice cloning system depends heavily on the quality and diversity of its training data.
But sourcing the right voice datasets isn’t simple. You need not only large volumes of audio recordings, but also variety in accents, dialects, emotions, and acoustic environments all collected ethically and with proper consent. That’s where specialised AI data providers come in.
To help you find the right partner, we’ve compiled a list of the top 8 providers of AI training data for voice cloning.
1. Twine AI
Twine AI specialises in custom, managed voice datasets. Rather than off-the-shelf corpora, Twine designs projects around client needs recruiting speakers by age, gender, region, or emotional tone. With built-in compliance (GDPR, CCPA) and strict QA, it ensures datasets are accurate, diverse, and ethically sourced.
Key strengths:
- Tailored voice data collection from 190+ countries across languages, accents, and tones.
- Compliance-first workflows with participant consent.
- Strong in voice AI, multilingual NLP, and multimodal datasets.
- Managed project delivery with full quality assurance.
2. Appen
Appen is one of the oldest and largest AI data providers, with broad coverage across 170+ languages and dialects. It offers both pre-built and custom voice datasets for training speech recognition and voice cloning systems.
Key strengths:
- One of the largest global crowdsourcing networks.
- Wide range of languages and accents.
- Longstanding industry reputation.
3. Defined.ai
Defined.ai offers both ready-made speech corpora via its marketplace and custom voice data collection services. It’s particularly strong in conversational AI and NLP datasets, helping clients train models for dialogue systems and assistants.
Key strengths:
- Marketplace for off-the-shelf speech corpora.
- Custom projects for accents, dialects, or scripted dialogue.
- Focus on ethical sourcing and dataset diversity.
4. Dataocean AI
Dataocean AI (formerly SpeechOcean) is a specialist in speech and language datasets, offering both pre-built and custom voice corpora. It has extensive coverage of tonal and non-tonal languages, making it valuable for global voice cloning projects.
Key strengths:
- Large catalogue of existing voice corpora.
- Custom dataset creation across many languages.
- Expertise in tonal language datasets (e.g., Mandarin, Thai).
5. DATAmundi.ai
DATAmundi.a (former Summa Linguae Technologies) focuses on real-world, contextual voice datasets, often collected in authentic environments to reflect natural acoustic conditions. This makes it particularly useful for building robust, production-ready voice cloning models.
Key strengths:
- Specialises in contextual, real-world speech collection.
- Coverage across multiple global languages.
- Experience in creating datasets for speech-enabled products.
6. iMerit
iMerit combines domain expertise with managed workforces to deliver curated voice datasets. Its teams handle transcription, segmentation, and annotation to ensure high-quality training-ready voice corpora.
Key strengths:
- Expertise in audio transcription and segmentation.
- Managed annotation workforce with QA pipelines.
- Domain-specific dataset support (healthcare, finance, etc.).
7. LXT
LXT provides multilingual voice datasets at scale, supported by a contributor base spanning 45+ languages. With ISO certifications and strong enterprise-grade processes, it’s a good fit for companies needing large, structured voice data collections.
Key strengths:
- Large-scale multilingual voice datasets.
- Strong compliance and data security standards.
- Suitable for enterprise-level speech AI projects.
8. Sama
Sama provides custom voice data annotation and curation with a focus on ethical sourcing. Known for its fair-trade approach to AI data, Sama ensures that every dataset meets quality, compliance, and transparency standards.
Key strengths:
- Ethical labour model with social impact.
- Strong expertise in audio transcription and labelling.
- Enterprise delivery with built-in QA.
Final Thoughts
Voice cloning is one of the fastest-growing applications of AI, but its success depends on having the right training data. High-quality custom datasets, built with diversity in accents, emotions, and environments, and collected with clear consent, are the foundation of accurate, reliable, and ethical models.
By choosing a provider that aligns with your project’s scale, compliance needs, and technical goals, you’ll be able to develop voice cloning systems that are not only realistic but also responsible and future-ready.
