This paper presents recent work on continuous speech labelling. We propose an original automatic labelling system where elementary phone models take a segmental analysis and the phone duration into account. These models are initialized by a short speaker-independent training stage in order to constitute a model database. From the standard phonetic transcription, phonological rules are gathered to process the various pronunciations. For each new corpus or speaker, a new quick unsupervised adaptation stage is performed to re-estimate the models, and then follows the correct labelling. We assess this system by labelling a difficult corpus (sequences of connected spelled letter) and sentences of one speaker of the BREF80 corpus. These results are quite promising, in the two experiments less than 9% of phonetic boundaries are incorrectly located.