PodCastle and Songle: Crowdsourcing-Based Web Services for Retrieval and Browsing of Speech and Music Content
Masataka Goto, Jun Ogata, Kazuyoshi Yoshii, Hiromasa Fujihara, Matthias Mauch, Tomoyasu Nakano · 2012
This paper describes two web services, PodCastle and Songle, that collect voluntary contributions by anonymous users in order to improve the experiences of users listening to speech and music content available on the web. These services use automatic speechrecognition and music-understanding technologies to provide content analysis results, such as full-text speech transcriptions and music scene descriptions, that let users enjoy content-based multimedia retrieval and active browsing of speech and music signals without relying on metadata. When automatic content analysis is used, however, errors are inevitable. PodCastle and Songle therefore provide an efficient error correction interface that let users easily correct errors by selecting from a list of candidate alternatives.