The aim of the present paper is to present a methodology to semi-automatically label large corpora. This methodology is based on three main points: using several concurrent automatic stochastic labellers, decomposing the labelling of the whole corpus into an iterative refining process and building a labelling comparison procedure which takes into account phonologic and acoustic-phonetic rules to evaluate the similarity of the various labelling of one sentence. After having detailed these three points, we describe our HMM-based labelling tool and we describe the application of that methodology to the Swiss French POLYPHON database.