A Semantic and Content Based Search User Interface for Browsing Large Collections of Foley Sounds
Sound designers select the sounds they use among massive collections of recordings. They usually rely on text based queries to narrow down a subset from these collections when looking for specific content. However, when it comes to unknown collections, this approach can fail to precisely retrieve files according to their content. We investigate an audio search engine that associates content based features and semantic meta data using Apache Solr deployed in a fully integrated server architecture. In order to facilitate the task of browsing the sounds, we also propose a search user interface in which the user can perform both text based queries and visual browsing in a window where sounds are organized according to their audio features. A preliminary evaluation of the performances helped to optimize the parameters of the system.
Audio Mostly Conference