In the last ten years, internet as well as its applications changed significantly, mainly thanks to the raising of available personal resources. Concerning multimedia, the most impressive evolution is the continuous growing success of the video sharing websites. But with this success come the difficulties to efficiently search, index and access relevant information about these documents. Speaker diariza-tion is an important task in the overall information retrieval process. This paper describes an audio/video database, especially built for the speaker diarization task, based on different video genres. Through some preliminary experiments, it highlights the difficulties encountered in this context, mainly linked to the database heterogeneity. Index Terms: speaker diarization, heterogeneous web videos, di-arization error rate