How Mindy Support Helped a Global Mobility Leader Build Native-Level Voice AI in 6 Languages

LLM Training Services, Speech Quality Evaluation with Corrective Feedback 

A global mobility platform needed to train its voice-based AI assistant to speak naturally – not just in multiple languages, but with authentic regional accents. The mission was clear: make the AI sound like a real native speaker across six diverse language environments.

To do this, the client launched a human-in-the-loop voice training initiative, and partnered with Mindy Support to manage the complex mix of speech data collection, linguistic evaluation, and expert feedback.

While their multilingual voice model could technically respond in multiple languages, it still sounded robotic, awkward, or non-native in many cases – especially across dialects like Egyptian Arabic or regional variants of Hindi. The client needed help to:

• Collect accent-accurate voice samples
  
• Score AI-generated speech for fluency, tone, and clarity
• Provide expert feedback to train the AI like a real language coach would

The client chose Mindy Support for our ability to rapidly scale native-speaking linguists, implement custom speech QA workflows, and coordinate effortlessly across multiple languages, time zones, and cultural regions. With a proven track record in large-scale LLM training and voice data evaluation, we offered both the linguistic depth and operational maturity needed for a project of this complexity.

From recruiting region-specific native speakers to delivering consistent, high-quality feedback workflows, our team brought:

• A multilingual workforce infrastructure built for scale

• Deep hands-on experience in LLM speech evaluation

• Agile project leadership and QA systems tailored to audio tasks

Our combined expertise in language, technology, and execution made us the ideal partner to help this multilingual voice AI sound truly native.

Mindy Support delivered end-to-end support for training a multilingual voice AI in six languages: Italian, Korean, German, Hindi, Egyptian Arabic, and Marathi. Our team handled:

• Native Accent Data Collection: Recruited fluent native speakers to record conversational prompts using authentic regional speech.

• Audio Evaluation & Scoring: Rated AI-generated responses on accent, pronunciation, intonation, fluency, and clarity using a structured rubric.

• Expert Feedback & Coaching: Trainers provided precise corrections like “soften the R sound” or “use more idiomatic phrasing” to fine-tune speech delivery.

• Voice Consistency Monitoring: Ensured the AI maintained a stable, human-like voice persona across all clips.

Each trainer completed three conversational loops (18 clips), creating an effective, iterative improvement cycle.

• Maintained >95% QA approval rate across all languages
• Submitted hundreds of corrective feedback entries
• Onboarded a multilingual team across 6 languages and dialects
• Helped transform robotic responses into natural, human-like speech — region by region