tailieunhanh - báo cáo hóa học:" Research Article An Ontological Framework for Retrieving Environmental Sounds Using Semantics and Acoustic Content"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article An Ontological Framework for Retrieving Environmental Sounds Using Semantics and Acoustic Content | Hindawi Publishing Corporation EURASIP Journal on Audio Speech and Music Processing Volume 2010 Article ID 192363 11 pages doi 2010 192363 Research Article An Ontological Framework for Retrieving Environmental Sounds Using Semantics and Acoustic Content Gordon Wichern Brandon Mechtley Alex Fink Harvey Thornburg and Andreas Spanias Arts Media and Engineering and Electrical Engineering Departments Arizona State University Tempe AZ 85282 USA Correspondence should be addressed to Gordon Wichern Received 1 March 2010 Accepted 19 October 2010 Academic Editor Andrea Valle Copyright 2010 Gordon Wichern et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Organizing a database of user-contributed environmental sound recordings allows sound files to be linked not only by the semantic tags and labels applied to them but also to other sounds with similar acoustic characteristics. Of paramount importance in navigating these databases are the problems of retrieving similar sounds using text- or sound-based queries and automatically annotating unlabeled sounds. We propose an integrated system which can be used for text-based retrieval of unlabeled audio content-based query-by-example and automatic annotation of unlabeled sound files. To this end we introduce an ontological framework where sounds are connected to each other based on the similarity between acoustic features specifically adapted to environmental sounds while semantic tags and sounds are connected through link weights that are optimized based on user-provided tags. Furthermore tags are linked to each other through a measure of semantic similarity which allows for efficient incorporation of out-of-vocabulary tags that is tags that do not yet exist in the database. Results on two freely available databases of environmental .