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

LIA-RAG: a system based on graphs and divergence of probabilities applied to Speech-To-Text Summarization