Visual Evaluation of Voice Transformation Based on Knowledge of Speaker

Voice transformation techniques are maturing. The ability to automatically change a source voice to a target voice, using a model built from a small amount of target speaker data, has brought with it the need to better understand how to evaluate the quality of a transformation model. This paper presents a simple experiment to measure how familiarity with the particular source and target speakers affects perception of the transformation. The results show that listeners' views of the transformation are not affected by familiarity with the speakers. In addition to these results, we also introduce transformation triangle diagrams, a graphical mechanism to better display certain relationships that are important in the evaluation of voice transformation