Prosody based Automatic Classification of the Uses of French 'Oui' as Convinced or Unconvinced Uses

摘要

When working with oral speech, the issue of natural meaning processing can be improved using easily available prosodic information. Only recently, semanticists have started to consider that the prosodic features could play a key role in the interpretation and classification of different word's uses. In this work, we propose a prosodic based automatic system that allows to classify the French word 'oui' into one of the classes 'conviction' or 'lack of conviction'. To that aim, a questionnaire inspired from opinion polls has been created and permitted to obtain 118 occurrences for both classes of 'oui'. Combined with feature selection procedure, the best classification rates decreases from 85.45% (speaker dependent mode) to 79.25% (speaker independent mode which is closer to an application). Interestingly, we also introduce the 'shuttle' principle that seeks to validate the semantic interpretation thanks to prosodic analysis.