A similar content retrieval method for podcast episodes

Abstract

Given podcasts (audio blogs) that are sets of speech files called episodes, this paper describes a method for retrieving episodes that have similar content. Although most previous retrieval methods were based on bibliographic information, tags, or users' playback behaviors without considering spoken content, our method can compute content-based similarity based on speech recognition results of podcast episodes even if the recognition results include some errors. To overcome those errors, it converts intermediate speech-recognition results to a confusion network containing competitive candidates, and then computes the similarity by using keywords extracted from the network. Experimental results with episodes that have different word accuracy and content showed that keywords obtained from competitive candidates were useful in retrieving similar episodes. To show relevant episodes, our method will be incorporated into PodCastle, a public web service that provides full-text searching of podcasts on the basis of speech recognition.