Real-Time Unsupervised Classification of Environmental Noise Signals

  title={Real-Time Unsupervised Classification of Environmental Noise Signals},
  author={Fatemeh Saki and Nasser Kehtarnavaz},
  journal={IEEE/ACM Transactions on Audio, Speech, and Language Processing},
This paper presents a real-time unsupervised classification of environmental noise signals without knowing the number of noise classes or clusters. A previously developed online frame-based clustering algorithm is modified by adding feature extraction, a smoothing step and a fading step. The developed unsupervised classification or clustering is examined in terms of purity of clusters and normalized mutual information. The results obtained for actual noise signals exhibit the effectiveness of… CONTINUE READING
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