In this paper we discuss the use of multi-layered tagsets for dialogue acts, in the context of dialogue understanding for multi-party meeting recording and retrieval applications. We discuss some desiderata for such tagsets and critically examine some previous proposals. We then define MALTUS, a new tagset based on the ICSI-MR and Switchboard tagsets, which satisfies these requirements. We present some experiments using MALTUS which attempt to compare the merits of integrated versus multi-level classifiers for the detection of dialogue acts.