Title : 
Accessing Minimal-Impact Personal Audio Archives
         
        
            Author : 
Ellis, Daniel P W ; Lee, Keansub
         
        
            Author_Institution : 
Columbia Univ.
         
        
        
        
        
        
        
            Abstract : 
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
         
        
            Keywords : 
Bayes methods; audio signal processing; information theory; pattern clustering; personal computing; Bayesian information criterion; audio labeling; audio segmentation; minimal-impact personal audio archive access; speaker segmentation; spectral clustering; Acoustic noise; Audio recording; Fourier transforms; Indexing; Loudspeakers; Robustness; Speech analysis; Speech recognition; Statistics; Video recording; audio clustering; audio segmentation; environment recognition; multimedia content analysis; personal archives;
         
        
        
            Journal_Title : 
MultiMedia, IEEE
         
        
        
        
        
            DOI : 
10.1109/MMUL.2006.75