  This paper aims to introduces a new algorithm for automatic speech-to-text
summarization based on statistical divergences of probabilities and graphs. The
input is a text from speech conversations with noise, and the output a compact
text summary. Our results, on the pilot task CCCS Multiling 2015 French corpus
are very encouraging
