5 citations · 7 across the 3 of their papers we have counts for
3 papers
Style Transfer and Extraction for the Handwritten Letters Using Deep Learning
Omar Mohammed, Gerard Bailly, Damien Pellier
How can we learn, transfer and extract handwriting styles using deep neural networks? This paper explores these questions using a deep conditioned autoencoder on the IRON-OFF handw…
Handwriting styles: benchmarks and evaluation metrics
Omar Mohammed, Gerard Bailly, Damien Pellier
Evaluating the style of handwriting generation is a challenging problem, since it is not well defined. It is a key component in order to develop in developing systems with more per…
A Variational Prosody Model for Mapping the Context-Sensitive Variation of Functional Prosodic Prototypes
Branislav Gerazov, Gérard Bailly, Omar Mohammed +2
The quest for comprehensive generative models of intonation that link linguistic and paralinguistic functions to prosodic forms has been a longstanding challenge of speech communic…