This paper is concerned with three types of causes leading to errors in a system using strictly speaker-independent rules for automatic extraction of linguistic information from measured prosodic parameters (PP) in read isolated sentences, in French: erroneous measurements of PP, duration and fun- damental frequency (type-1 errors); differences between speakers who do not fit into the same prosodic moult (type-2 problems) and certain combination of segmental influences on duration, which cannot be factored out in a strictly bottom-up system (type-3 problems). It suggests that neither further tuning of the existing rules, nor statistical learning are complete solutions. Type-1 errors are extrinsic to the prosodic module and can be hardly improved. An effective way of reducing incertainties due to type-2 problems is a partial tuning of the set of rules to the particular habits of the speaker: adaptation is feasible because there is a remarkable intra-speaker consistency in prosodic patterning, at least in serially read isolated sentences. Type-3 errors leads to multiple solutions in certain cases. It is necessary therefore to model to a certain extent the inter-speaker variability.
Bibliographic reference. Vaissière, Jacqueline (1989): "On automatic extraction of prosodic information for automatic speech recognition system", In EUROSPEECH-1989, 1202-1205.