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