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Modern TV or radio news talk-shows include a variety of sequences which comply with specific journalistic patterns, including debates, interviews, reports. The paper deals with automatic chapter generation for TV news talk-shows, according to these different journalistic genres. It is shown that linguistic and speaker-distribution based features can lead to an efficient characterization of these genres when the boundaries of the chapters are known, and that a speaker-distribution based segmentation is suitable for segmenting contents into these different genres. Evaluations on a collection of 42 episodes of a news talk-show provided by the French evaluation campaign REPERE show promising performance.