Validation of an AI-assisted Treatment Outcome Measure for Gender-Affirming Voice Care: Comparing AI Accuracy to Listener ’s Perception of Voice Femininity

There is currently a lack of objective treatment outcome measures for transgender individuals undergoing gender-affirming voice care. Recently, Bensoussan et al developed an AI model that is able to generate a voice femininity rating based on a short voice sample provided through a smartphone application. The purpose of this study was to examine the feasibility of using this model as a treatment outcome measure by comparing its performance to human listeners. Additionally, we examined the effect of two different training datasets on the model ’s accuracy and performance when presented with external data.

Source: Journal of Voice - December 29, 2023 Category: ENT & OMF Authors: Shane Simon, Einav Silverstein, Lauren Timmons-Sund, Jeremy M. Pinto, Eugenia M. Castro, Karla O ’Dell, Michael M. Johns III, Wendy J. Mack, Yael Bensoussan Source Type: research