A new study published in *Nature Human Behaviour* reveals the intricate neural pathways involved in everyday conversation. Researchers, led by Dr. Ariel Goldstein from the Hebrew University of Jerusalem, Google Research, the Hasson Lab at Princeton University, and NYU Langone Comprehensive Epilepsy Center, analyzed over 100 hours of brain activity using electrocorticography (ECoG) during real-life discussions. The study employed the Whisper speech-to-text model to deconstruct language into sounds, speech patterns, and semantic meanings.
Results indicate the brain processes language sequentially: from conceptualizing words to articulating sounds when speaking, and from phonetic recognition to understanding meaning when listening. The computational framework developed could predict brain activity with high accuracy, even in conversations outside the original dataset.
This research offers potential advancements in speech recognition technology and communication tools for individuals with communication impediments.