Detecting applause in both audio recordings and real-time performances is relevant in such applications as music information retrieval and spatial audio coding. A combination of mel-frequency cepstral coefficients and low-level descriptors yielded the best classification performance in the experiments. Low-pass filtering of the feature time series leads to the concept of sigma features. Binary misclassification occurs more often when applause and nonapplause with similar amplitudes are simultaneously present.
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