Unlocking the Silent Mind: Using Brain Signals and AI to Decode Inner Speech in Individuals with Congenital Speech and Hearing Impairments

解锁无声思维：利用脑信号与人工智能解读先天言语和听觉障碍者的内在语言

100000

Congenital Speech and Hearing Impairments present profound challenges in communication, cognitive development, and social integration. While assistive technologies like cochlear implants and speech therapy exist, they remain insufficient for individuals who have never acquired spoken language. A crucial but underexplored aspect of congenital speech and hearing impairments is inner speech, which is the silent and internal dialogue shaping cognition, self-regulation, and problem-solving. This research aims to bridge this gap by leveraging Electroencephalography and Brain-Computer Interface technologies to decode inner speech neural signals in individuals with congenital speech and hearing impairments. By employing deep learning models, we will analyze electroencephalography signals to uncover non-verbal cognitive communication mechanisms. Understanding these patterns can revolutionize assistive communication technologies and offer a new pathway for those who cannot speak or hear. This study pioneers an artificial intelligence driven approach to unlocking inner speech with profound implications for neuroscience, cognitive psychology, and assistive communication. It ultimately fosters greater inclusivity and accessibility for individuals with congenital speech and hearing impairments.