Mixed-EVC: Mixed Emotion Synthesis and Control in Voice Conversion

Understand

Emotional voice conversion (EVC) traditionally targets the transformation of spoken utterances from one emotional state to another, with previous research mainly focusing on discrete emotion categories.

• This paper departs from the norm by introducing a novel perspective: a nuanced rendering of mixed emotions and enhancing control over emotional expression.
• To achieve this, we propose a novel EVC framework, Mixed-EVC, which only leverages discrete emotion training labels.
• We construct an attribute vector that encodes the relationships among these discrete emotions, which is predicted using a ranking-based support vector machine and then integrated into a sequence-to-sequence (seq2seq) EVC framework.