Abstract:

The method of “sparse representations,” based on the idea that observations should be represented by only a few items chosen from a large number of possible items, has emerged recently as an interesting approach to the analysis of image s and audio. New theoretical advances and practical algorithms mean that the sparse representations approach is becoming a potentially powerful signal processing and analysis method. Some of the key concepts in sparse representations will be introduced, including algorithms to find sparse representations of data. An overview of some applications of sparse representations in audio will be described, including for automatic music transcription and audio source separation, and pointers will be given for possible future directions in this area. [This work has been supported by grants and studentships from the UK Engineering and Physical Sciences Research Council.]