Enhancing the Self-Other Voice Discrimination Procedure for Clinical Applications

Self-voice plays an important role in our everyday lives. Apart from being used for communication, our own voice defines our identity, as it is the sound that is most intimately related to ourselves. Disturbances in self-voice recognition have been related to certain psychotic symptoms such as auditory-verbal hallucinations, colloquially called ‘hearing voices’, and to a distorted sense of self more generally. Recent research has indicated that a specific self-other voice discrimination procedure combining psychophysics, voice morphing technology, as well as air-and bone-conducted voice stimuli can be of clinical significance as a biomarker for detecting pathological alterations in self-consciousness. However, there are several limitations with the existing approach, mainly in not being simple to use and difficult to apply in different clinical contexts. To address these drawbacks, we adapted the current methodology and developed a self-other voice discrimination solution with a graphical user interface, automated voice morphing with personalized voice selection tool, and results visualization. This improves the usability of the task, shortens the procedure duration, and provides a patient-tailored approach. This paper demonstrates the technological advantages and scientific potential of the new methodology, with sample data from two different participant groups in clinical and non-clinical settings.