Yann Morlec

Learn More
The majority of research in the analysis and generation of prosody for use in speech synthesis systems has focused on prosodic features that ease the syntactic parsing of an utterance or highlight certain parts of it. It is well-known that prosody-and especially final lengthening in French – may reflect very fine and complex attributes of the syntactic(More)
We present here a trainable generative model of French prosody. We focus on the sentence level and design SNNs able to generate both rhythmic and intonation contours for diverse attitudes. First results of a perceptual test show that listeners are able to retrieve the right definition of attitudes by listening to synthetic PSOLA stimuli. In our theoretical(More)
A dynamic model for synthesizing intonation is presented. This model is based on the following assumptions: intonation is the result of superposed and independent prototypical gestures belonging to diverse linguistic levels: sentence, clause, group, subgroup ... Prototypical movements are progressively stored in a prosodic lexicon and used by the speaker in(More)
A data-driven method based on a new paradigm is introduced in this paper. We assume that cognitive representations of the discourse are prosodically encoded by means of global multiparametric prototypes. The generation of adequate prosodic contours is then obtained by retrieving and combining these elementary prototypic contours accessed by linguistic or(More)
The topic of this paper concerns automatic training of prosody for a text-to-speech synthesis system. We propose a method that permits the system to be specialised for a concrete application by training it on a representative corpus of data for that application. Design, training and evaluation of the system is carried out for an application concerning the(More)
  • 1