Boris Defreville

The "bag-of-frames" approach (BOF), which encodes audio signals as the long-term statistical distribution of short-term spectral features, is commonly regarded as an effective and sufficient way to represent environmental sound recordings (soundscapes) since its introduction in an influential 2007 article. The present paper describes a concep-tual replication of this seminal article using several new soundscape datasets, with results strongly questioning the adequacy of the BOF approach for the task. We show that the good accuracy originally re-ported with BOF likely result from a particularly thankful dataset with low within-class variability, and that for more realistic datasets, BOF in fact does not perform significantly better than a mere one-point av-erage of the signal's features. Soundscape modeling, therefore, may not be the closed case it was once thought to be. Progress, we ar-gue, could lie in reconsidering the problem of considering individual acoustical events within each soundscape.

The “bag-of-frames” (BOF) approach, which encodes audio signals as the long-term statistical distribution of short-term spectral features, is commonly regarded as an effective and sufficient way to represent environmental sound recordings (soundscapes). The present paper describes a conceptual replication of a use of the BOF approach in a seminal article using several other soundscape datasets, with results strongly questioning the adequacy of the BOF approach for the task. As demonstrated in this paper, the good accuracy originally reported with BOF likely resulted from a particularly permissive dataset with low within-class variability. Soundscape modeling, therefore, may not be the closed case it was once thought to be.