6-Language Audio & Video Data Collection Project Powering Next-Gen Speech Translation AI

Audio & Video Data Collection, Multilingual Transcription, Scenario Design, Quality Assurance

Our client is a U.S.-based deep tech company pioneering AI-driven voice technologies for the enterprise, consumer electronics, and automotive sectors. Their solutions power interactive voice agents, embedded systems, and multimodal interfaces used by millions of people worldwide.Their vision: to build machines that don’t just communicate intelligently – but intuitively.They’re developing AI that can understand accents, contexts, and emotional tones in real time.To do that, they needed one thing above all – data that speaks like humans do.

Existing datasets weren’t enough. They were synthetic, inconsistent, and linguistically narrow.For robust speech translation and automatic speech recognition (ASR) models, the client required data that captured the full diversity of human speech:

• Native-level fluency across six languages (German, Italian, Hindi, Ukrainian, Modern Standard Arabic, Russian)
• Balanced gender, age, and accent distribution
• High-quality lecture and dialogue recordings reflecting real-world acoustic conditions
• Time-aligned, high-accuracy transcriptions (95%+ accuracy, ≤5% WER/TER)
• Full compliance with data ethics and privacy standards

And it all needed to be delivered at scale, without compromising linguistic authenticity or technical precision.

Mindy Support was chosen for our proven ability to build large-scale, high-quality speech datasets for AI and R&D teams worldwide.The client needed a partner with global reach, technical discipline, and linguistic expertise – and that’s exactly what we provided. They valued our:

• Global native speaker network spanning 50+ languages and accents
• Deep expertise in audio data engineering and transcription QA
• Proven workflow for lecture & dialogue scenario creation
• ISO 27001-certified infrastructure and secure AWS S3 delivery
• Agile project management with real-time client feedback loops
  

We didn’t just record voices – we built a multilingual speech evaluation framework from scratch:

1/Speaker Recruitment & Scenario Design:
We sourced and verified native experts and professional interviewers across six target languages. Our team created culturally relevant lecture and dialogue scripts on socially significant topics – ensuring factual, unbiased, and engaging speech content.

2/Audio & Video Collection
Each session included a 10-20 minute lecture and a 10-20 minute expert-interviewer dialogue. Recordings followed strict specifications:

• Full HD (1920×1080), professional attire, green-screen backdrop
• Stereo audio, 16–48 kHz, split-channel recording (expert right / interviewer left)
• Audio: WAV | Video: MP4

3/Transcription & Quality Control:
Our linguistic QA team transcribed and validated each file with 95%+ accuracy, using a custom Voice Activity Detection (VAD) tool for precise timing.Multiple review cycles ensured transcription alignment, accent authenticity, and formatting consistency.

4/Final Packaging & Delivery:
All assets – audio, video, and TSV transcripts – were securely delivered via AWS S3, fully anonymized and ready for machine learning ingestion.

• Dataset Scale:
  36+ experts and interviewers across 6 languages
  Dozens of lecture and dialogue recordings totaling several hours of validated speech data.
• Quality Metrics:
  95%+ transcription accuracy (≤5% WER/TER)
  Accent and linguistic authenticity confirmed across all languages.
• Data Diversity:
  Balanced gender ratio (50:50 ±10%), multiple domains and accents.
• Delivery Speed:
  End-to-end project execution within tight R&D timelines.
• Impact:
  Enabled the client to build a robust evaluation corpus for ASR benchmarking
  Improved speech translation model performance and cross-lingual understanding
  Strengthened the foundation for emotionally aware, multilingual voice AI.