Machine Translation Generative AI
Human-Curated Translation for Bias Mitigation in Machine Translation Technology
The Challenge
LLM developers often rely on public datasets for standard benchmark performance measurement or to create custom datasets. While public datasets are easily accessible and low-cost, they may have already been processed or memorized by large language models during training, undermining their usefulness for evaluation.
Our client—one of the world’s leading developers of generative AI tools—required a robust dataset to assess the performance of their translation system across multiple languages. Their existing suppliers used machine-generated translations to create test and training datasets, compromising both the integrity of the evaluation process and the accuracy of the translation engine.
The client needed a trusted partner to provide large-scale, human-validated, bias-mitigated translations aligned with the Massive Multitask Language Understanding (MMLU) benchmark. They chose DataForce based on our proven track record in delivering high-quality, fit-for-purpose translations at scale.
• • • •The Solution• • • •
DataForce assembled a global team of professional linguists to translate and validate more than 15 million words across 14 underrepresented languages. A strict requirement was that no machine translation could be used (to preserve dataset purity and eliminate potential model contamination). This presented a unique challenge, as machine translation tools are widely accessible and their outputs can closely resemble human work.
To ensure translation authenticity and data integrity, DataForce implemented a multi-layered quality assurance approach:
- Controlled Work Environment:
- Translators worked within a proprietary platform that prevented copy-pasting and restricted access to external tools.
- Automated Detection:
- A custom-built similarity evaluation tool compared translations against outputs from the five most widely used machine translation engines, flagging potential policy breaches.
- Manual Review:
- A team of experienced reviewers manually audited flagged segments to identify patterns indicative of machine-generated content.
Through centralized project management and continuous monitoring, we achieved 100% compliance and delivered the full 15-million-word corpus within just nine weeks.
Regular check-ins and open communication with the client ensured alignment with evolving needs and process refinements throughout the engagement.
Results
In just nine weeks, DataForce delivered:
- Over 1 million words translated per language across 14 languages, totaling more than 15 million words
- 100% human translation and expert linguistic review
- Strengthened machine translation system performance, enabling more accurate and trustworthy evaluation
By combining expert linguists, proprietary tools, and secure project infrastructure, we helped the client restore confidence in their machine translation testing process—supporting the development of more accurate and unbiased AI systems.