Note: This bibliographic page is archived and will no longer be updated. For an up-to-date list of publications from the Music Technology Group see the Publications list .

Environmental sound recognition using short-time feature aggregation

Title Environmental sound recognition using short-time feature aggregation
Publication Type Journal Article
Year of Publication 2017
Authors Roma, G. , Herrera P. , & Nogueira W.
Journal Title Journal of Intelligent Information Systems
Pages 1-19
Journal Date 08/2017
ISSN 1573-7675
Final publication 10.1007/s10844-017-0481-4
Original Publication
Additional material:
Recognition of environmental sound is usually based on two main architectures, depending on whether the model is trained with frame-level features or with aggregated descriptions of acoustic scenes or events. The former architecture is appropriate for applications where target categories are known in advance, while the later affords a less supervised approach. In this paper, we propose a framework for environmental sound recognition based on blind segmentation and feature aggregation. We describe a new set of descriptors, based on Recurrence Quantification Analysis (RQA), which can be extracted from the similarity matrix of a time series of audio descriptors. We analyze their usefulness for recognition of acoustic scenes and events in addition to standard feature aggregation. Our results show the potential of non-linear time series analysis techniques for dealing with environmental sounds.