6 citations · 8 across the 3 of their papers we have counts for
4 papers
On granularity of prosodic representations in expressive text-to-speech
Mikolaj Babianski, Kamil Pokora, Raahil Shah +3
In expressive speech synthesis it is widely adopted to use latent prosody representations to deal with variability of the data during training. Same text may correspond to various…
GaLeNet: Multimodal Learning for Disaster Prediction, Management and Relief
Rohit Saha, Mengyi Fang, Angeline Yasodhara +7
After a natural disaster, such as a hurricane, millions are left in need of emergency assistance. To allocate resources optimally, human planners need to accurately analyze data th…
Non-Autoregressive TTS with Explicit Duration Modelling for Low-Resource Highly Expressive Speech
Raahil Shah, Kamil Pokora, Abdelhamid Ezzerg +5
Whilst recent neural text-to-speech (TTS) approaches produce high-quality speech, they typically require a large amount of recordings from the target speaker. In previous work, a 3…
Low-resource expressive text-to-speech using data augmentation
Goeric Huybrechts, Thomas Merritt, Giulia Comini +3
While recent neural text-to-speech (TTS) systems perform remarkably well, they typically require a substantial amount of recordings from the target speaker reading in the desired s…