A methodology for the automatic detection of perceived prominent syllables in spoken French

Abstract

Prosodic transcription of spoken corpora relies mainly on the identification of perceived prominence. However, the manual annotation of prominent phenomena is extremely timeconsuming, 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 1. a spontaneous French corpus that has been manually annotated according to a strict methodology and 2. some acoustic prosodic parameters, shown to be corpusindependent, that are used to detect prominent syllables. Some automatic tools, used to handle large corpora, are also described.