“Phonetic sourcing and acoustic slicing for localized voice models”
Partnering with Google's global conversational-AI teams, Lotus Avio engineered a massive, high-fidelity phonetic speech-and-linguistic database to power next-generation localized voice-recognition and text-to-speech models.
Generative voice networks are hyper-sensitive to any acoustic footprint — ordinary room reflection distorts consonants and vocal decays and hampers linguistic alignment. Recording out of our custom-isolated Acoustic Vocal Suite B, with calculated resonance absorption and floating decoupling traps, we pushed reverberation down to RT60 < 0.1 seconds and delivered pristine, model-ready datasets with careful transcription and QA at scale.
Our campaign strategy
Near-zero room reflection
A custom-isolated vocal suite with resonance absorption and floating decoupling traps, holding RT60 below 0.1 seconds.
Phonetic speaker panel
A broad panel of speakers captured for balanced phonetic coverage across accents and vocal distributions.
Acoustic slicing & alignment
High-volume linguistic sound-acoustic slicing with word-level transcript alignment for clean training pairs.
Uncompressed studio masters
Uncompressed, studio-grade capture with rigorous QA before delivery in model-ready formats.
