  This paper introduces the notion of qualitative belief assignment to model
beliefs of human experts expressed in natural language (with linguistic
labels). We show how qualitative beliefs can be efficiently combined using an
extension of Dezert-Smarandache Theory (DSmT) of plausible and paradoxical
quantitative reasoning to qualitative reasoning. We propose a new arithmetic on
linguistic labels which allows a direct extension of classical DSm fusion rule
or DSm Hybrid rules. An approximate qualitative PCR5 rule is also proposed
jointly with a Qualitative Average Operator. We also show how crisp or interval
mappings can be used to deal indirectly with linguistic labels. A very simple
example is provided to illustrate our qualitative fusion rules.
