In this paper, we aim to improve the classification of human non-speech sounds produced in a meeting-room environment by using concepts and tools from the fuzzy theory. Starting with an SVM-based baseline system, firstly a reduction of the number of features with the fuzzy measure is shown. And, secondly, a noticeable improvement of the classification performance is reported by combining the outputs of two classification systems with the fuzzy integral.