Fast query by example of environmental sounds via robust and efficient cluster-based indexing

There has been much recent progress in the technical infrastructure necessary to continuously characterize and archive all sounds, or more precisely auditory streams, that occur within a given space or human life. Efficient and intuitive access, however, remains a considerable challenge. In specifically musical domains, i.e., melody retrieval, query-by-example (QBE) has found considerable success in accessing music that matches a specific query. We propose an extension of the QBE paradigm to the broad class of natural and environmental sounds, which occur frequently in continuous recordings. We explore several cluster-based indexing approaches, namely nonnegative matrix factorization (NMF) and spectral clustering to efficiently organize and quickly retrieve archived audio using the QBE paradigm. Experiments on a test database compare the performance of the different clustering algorithms in terms of recall, precision, and computational complexity. Initial results indicate signifi...

• Type: Conference
• Year: 2008
• Where: ICASSP
• Authors: Jiachen Xue, Gordon Wichern, Harvey D. Thornburg, Andreas Spanias
• Keywords: Environmental Sounds, ICASSP 2008, Nonnegative Matrix Factorization, QBE Paradigm, Signal Processing