Abstract
The article presents an approach to environmental sound recognition that uses selected methods from the field of digital image processing and recognition. The proposed technique adopts the assumption that an audio signal can be converted into a visual representation, and processed further, as an image. At the first stage the audio data are converted into rectangular matrices called feature maps. Then a two-step approach is applied: the construction of a representative database of reference samples and the identification of test samples. The process of building the database employs two-dimensional linear discriminant analysis. Then the recognition operation is carried out in a reduced feature space that has been obtained by two-dimensional Karhunen–Loeve projection. At the classification stage, a minimum distance classifier is applied to different features. As it is shown, the results are very encouraging and can be a base for many practical audio applications.
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Maka, T., Forczmański, P. (2016). Environmental Sounds Recognition Based on Image Processing Methods. In: Burduk, R., Jackowski, K., Kurzyński, M., Woźniak, M., Żołnierek, A. (eds) Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015. Advances in Intelligent Systems and Computing, vol 403. Springer, Cham. https://doi.org/10.1007/978-3-319-26227-7_68
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DOI: https://doi.org/10.1007/978-3-319-26227-7_68
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