Probabilistic amplitude demodulation.
In: Davies, ME and James, CJ and Abdallah, SA and Plumbley, MD, (eds.)
Independent Component Analysis and Signal Separation, Proceedings.
(pp. 544 - 551).
Auditory scene analysis is extremely challenging. One approach, perhaps that adopted by the brain, is to shape useful representations of sounds on prior knowledge about their statistical structure. For example, sounds with harmonic sections are common and so time-frequency representations are efficient. Most current representations concentrate on the shorter components. Here, we propose representations for structures on longer time-scales, like the phonemes and sentences of speech. We decompose a sound into a product of processes, each with its own characteristic time-scale. This demodulation cascade relates to classical amplitude demodulation, but traditional algorithms fail to realise the representation fully. A new approach, probabilistic amplitude demodulation, is shown to out-perform the established methods, and to easily extend to representation of a full demodulation cascade.
|Title:||Probabilistic amplitude demodulation|
|Event:||7th International Conference on Independent Component Analysis and Signal Separation|
|Dates:||2007-09-09 - 2007-09-12|
|Keywords:||audio processing, dynamic and temporal models, hierarchical models, sparse representations, unsupervised learning|
|UCL classification:||UCL > School of Life and Medical Sciences > Faculty of Life Sciences > Gatsby Computational Neuroscience Unit|
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