Estimating subglottal pressure and vocal fold adduction from the produced voice in a single-subject study (L).

We previously reported a simulation-based neural network for estimating vocal fold properties and subglottal pressure from the produced voice. This study aims to validate this neural network in a single-human subject study. The results showed reasonable accuracy of the neural network in estimating the subglottal pressure in this particular human subject. The neural network was also able to qualitatively differentiate soft and loud speech conditions regarding differences in the subglottal pressure and degree of vocal fold adduction. This simulation-based neural network has potential applications in identifying unhealthy vocal behavior and monitoring progress of voice therapy or vocal training.