Microphone arrays are useful in meeting rooms, where speech needs to be acquired and segmented. For example, automatic speech segmentation allows enhanced browsing experience, and facilitates automatic analysis of large amounts of data. Spontaneous multi-party speech includes many overlaps between speakers; moreover other audio sources such as laptops and projectors can be active. For these reasons, locating multiple wideband sources in a reasonable amount of time is highly desirable. In existing multisource localization approaches, search initialization is very often an issue left open. We propose here a methodology for estimating speech activity in a given sector of the space rather than at a particular point. In experiments on more than one hour of speech from real meeting room multisource recordings, including loudspeakers as well as human speakers, we show that the sector-based approach greatly reduces the search space. At the same time, it achieves effective localization of multiple concurrent speakers.