This paper presents a method for combining audio similarity and semantic similarity into a single similarity measure for query-by-example retrieval. The integrated similarity measure is used to retrieve sound events that are similar in content to the given query and have labels containing similar words. Through the semantic component, the method is able to handle variability in labels of sound events. Through the acoustic component, the method retrieves acoustically similar examples. On a test database of over 3000 sound event examples, the proposed method obtains a better retrieval performance than audio-based retrieval, and returns results closer acoustically to the query than a label-based retrieval.
['Annamaria Mesaros', 'Toni Heittola', 'Kalle J. Palomäki']
Query-by-example retrieval of sound events using an integrated similarity measure of content and label