Podcast Metadata and Content: Episode Relevance andAttractiveness in Ad Hoc Search

TL;DR

This paper investigates methods for indexing and retrieving relevant podcast content using metadata and transcripts to improve ad hoc search effectiveness in large, diverse archives.

Contribution

It introduces diverse information needs and evaluates different approaches for assessing relevance, providing recommendations for podcast content retrieval systems.

Findings

Metadata and transcripts both aid relevance detection

Different approaches vary in effectiveness depending on content type

Recommendations improve podcast search accuracy

Abstract

Rapidly growing online podcast archives contain diverse content on a wide range of topics. These archives form an important resource for entertainment and professional use, but their value can only be realized if users can rapidly and reliably locate content of interest. Search for relevant content can be based on metadata provided by content creators, but also on transcripts of the spoken content itself. Excavating relevant content from deep within these audio streams for diverse types of information needs requires varying the approach to systems prototyping. We describe a set of diverse podcast information needs and different approaches to assessing retrieved content for relevance. We use these information needs in an investigation of the utility and effectiveness of these information sources. Based on our analysis, we recommend approaches for indexing and retrieving podcast content for ad hoc search.