Interpolation of Perceived Gender in Speech Signals

Abstract: For individuals with gender dysphoria, voice therapy can be an important tool to change characteristics about their voice to align better with their gender identity. This is often done by practising with a speech therapist and can be a long and difficult process. A useful tool in this setting would be software that can generate a voice, based on the patients voice, which lies slightly closer to their desired voice. The patient could then mimic the generated voice in order to train their voice. The purpose of this thesis is to explore how voices can be digitally modified in order to change how their gender is perceived. The aim is to find a method of interpolation where a voice could gradually be modified to sound like a target voice, and where all intermediate points on the path sound natural. Two methods were evaluated, but only one produced adequate results that were evaluated with a participant survey. Survey participants listened to voices that are a mix of female and male voices, and rated on a scale how they perceived the gender and if the voices sounded natural. The results show that there is a decrease in how natural the modified voices sound. On average there is a consensus that the perceived gender is changed, however the individual participant results showed that there is a need for improvement.