2026
ParaMETA: Towards Learning Disentangled Paralinguistic Speaking Styles Representations from Speech
AAAI 2026technical
Learning representative embeddings for different types of speaking styles, such as emotion, age, and gender, is critical for both recognition tasks (e.g., cognitive computing and human-computer interaction) and generative tasks (e.g., style-controllable speech generation). In this work, we introduce