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eess.AS2024
Deep Speech Synthesis from Multimodal Articulatory Representations
Peter Wu, Bohan Yu, Kevin Scheck +6
The amount of articulatory data available for training deep learning models is much less compared to acoustic speech data. In order to improve articulatory-to-acoustic synthesis pe…
eess.AS2024
Investigating Effective Speaker Property Privacy Protection in Federated Learning for Speech Emotion Recognition
Chao Tan, Sheng Li, Yang Cao +2
Federated Learning (FL) is a privacy-preserving approach that allows servers to aggregate distributed models transmitted from local clients rather than training on user data. More…