Combining semantic, social, and acoustic similarity for retrieval of environmental sounds

Abstract

Recent work in audio information retrieval has demonstrated the effectiveness of combining semantic information, such as descriptive, tags with acoustic content. However, these methods largely ignore the possibility of tag queries that do not yet exist in the database and the possibility of similar terms. In this work, we propose a network structure integrating similarity between semantic tags, content-based similarity between environmental audio recordings, and the collective sound descriptions provided by a user community. We then demonstrate the effectiveness of our approach by comparing the use of existing similarity measures for incorporating new vocabulary into an audio annotation and retrieval system.

An architecture for retrieval of animal sound recordings based on context variables

“…Also, focusing on semantic similarity, Mechtley et al proposed to use words from WordNet to allow users to tag sounds. They incorporate these tags to find semantic similarity among the concepts used to describe sounds and proposed a network structure for integrating similarity between the semantic tags.…”