Abstract : A fine-grained segmentation of Radio or TV broadcasts is an essential step for most multimedia processings. Applying seg- mentation algorithms to the speech transcripts seems straight- forward. Yet, most of these algorithms are not suited when dealing with short segments or noisy data. In this paper, we propose a new segmentation technique inspired from the im- age segmentation field and relying on a new way to compute similarities between candidate segments. This new topic seg- mentation technique is evaluated on two corpora of French TV broadcasts on which it largely outperforms other existing ap- proaches from the state-of-the-art.