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The description of the acoustic activity in a room environment has to face the problem of overlapped sounds, i.e. those which occur simultaneously. That problem can be tackled by carrying out some kind of source signal separation followed by the detection and recognition of the identity of each of the overlapped sounds. An alternative approach relies on modeling all possible overlapping combinations of acoustic events. For a spatial scene description, there is still the need of assigning each of the detected acoustic events to one of the estimated source positions. Both detection approaches are tested in our work for the case of two simultaneous sources, one of which is speech, and an array of three microphones. Blind source separation based on the deflation method and null steering beamforming are used for signal separation. Also a position assignment system is developed and tested in the same experimental scenario. It is based on the above mentioned beamformer and takes the decision based on a likelihood ratio. Both signal-level fusion and likelihood fusion are tried to combine the information from the two pairs of microphones. The reported experimental results illustrate the possibilities of the various implemented techniques.