Accessing Minimal-Impact Personal Audio Archives
Daniel P. W. Ellis, Keansub Lee · IEEE Multimedia · 2006
We've collected personal audio - essentially everything we hear - for two years and have experimented with methods to index and access the resulting data. Here, we describe our experiments in segmenting and labeling these recordings into episodes (relatively consistent acoustic situations lasting a few minutes or more) using the Bayesian information criterion (from speaker segmentation) and spectral clustering