Multilingual Speech & Dialect Audio Data Collection in India

Building production Automatic Speech Recognition (ASR), Text-to-Speech (TTS), and Large Audio Models (LAMs) for global and regional deployments requires diverse, real-world voice data. India’s linguistic landscape — spanning 22 official languages and over 700 regional dialects — presents the ultimate benchmark for voice AI robustness.

Our Speech & Audio Data Collection Capabilities

Blue Projects deploys field teams with studio-grade microphone arrays, lapel mics, and mobile recording hardware across Tier 1 to Tier 4 regions in India to capture high-fidelity audio:

• Indic Multilingual Corpus: Scripted, semi-spontaneous, and natural conversational audio across Hindi, Kannada, Tamil, Telugu, Marathi, Bengali, Malayalam, Gujarati, and English (Indian Accents).
• Acoustic Environment Diversity: Far-field, near-field, vehicular, industrial plant background noise, and street environment recordings for noise-robust ASR training.
• Phonetic & Timed Transcriptions: Verbatim phonetic transcribing, speaker diarization, timestamps, and emotion/intent tagging by native speaker annotators.