Vers un algorithme de détection (semi-) automatique des proéminences en français parlé

International audienceProsodic transcription of spoken corpora relies mainly on the identification of perceived prominence. However, the manual annotation of prominent phenomena is extremely time-consuming, and varies greatly from one expert to another. Automating this procedure would be of great importance. In this study, we present the first results of a methodology aiming at an automatic detection of prominence syllables. It is based on (i) a spontaneous French corpus that has been manually annotated according to a strict methodology and (ii) some acoustic prosodic parameters, shown to be corpus-independent, that are used to detect prominent syllables. Some automatic tools, used to handle large corpora, are also described