Live Breaking News & Updates on Robust Speech Recognition

Speech neuroprostheses have the potential to restore communication to people living with paralysis, but naturalistic speed and expressivity are elusive1. Here we use high-density surface recordings of the speech cortex in a clinical-trial participant with severe limb and vocal paralysis to achieve high-performance real-time decoding across three complementary speech-related output modalities: text, speech audio and facial-avatar animation. We trained and evaluated deep-learning models using neural data collected as the participant attempted to silently speak sentences. For text, we demonstrate accurate and rapid large-vocabulary decoding with a median rate of 78 words per minute and median word error rate of 25%. For speech audio, we demonstrate intelligible and rapid speech synthesis and personalization to the participant’s pre-injury voice. For facial-avatar animation, we demonstrate the control of virtual orofacial movements for speech and non-speech communic ....

United States , Paulh Brookes , Jd Organization , International Conference On Learning Representations , Pacific Rim Conference On Communications Computers , International Conference On Machine , Virtual User Forum , Curran Associates , Association For Computational Linguistics , International Conference On Machine Learning Vol , International Conference On Neural Information Processing Systems , Workshop At International Conference On Learning Representations , International Conference On Acoustics , International Brain , Information Processing Association Annual Summit , Brain Computer Interface , Alternative Communication , International Conference , New Era , Robust Speech Recognition , Exploiting Deep , Neural Eng , Audio Speech , Signal Processing , Amazon Mechanical , Implicit Communication ,