Ammar Abbas — accepted AI-conference papers

2021

Camp: A Two-Stage Approach to Modelling Prosody in Context

Zack Hodari, Alexis Moinet, Sri Karlapati, Jaime Lorenzo-Trueba, Thomas Merritt, Arnaud Joly +3

ICASSP 2021accepted

Prosody is an integral part of communication, but remains an open problem in state-of-the-art speech synthesis. There are two major issues faced when modelling prosody: (1) prosody varies at a slower rate compared with other content in the acoustic signal (e.g. segmental information and background n…

Cited by 33 Source ↗Scholar ↗

2021

Prosodic Representation Learning and Contextual Sampling for Neural Text-to-Speech

Sri Karlapati, Ammar Abbas, Zack Hodari, Alexis Moinet, Arnaud Joly, Penny Karanasou +1

ICASSP 2021accepted

In this paper, we introduce Kathaka, a model trained with a novel two-stage training process for neural speech synthesis with contextually appropriate prosody. In Stage I, we learn a prosodic distribution at the sentence level from mel-spectrograms available during training. In Stage II, we propose…

Cited by 0 Source ↗Scholar ↗