Overview - Podcast 2020

Proceedings | Data | Results | Runs | Participants

The Podcast Track is new at the Text Retrieval Conference (TREC) in 2020. The podcast track was designed to encourage research into podcasts in the information retrieval and NLP research communities. The track consisted of two shared tasks: segment retrieval and summarization, both based on a dataset of over 100,000 podcast episodes (metadata, audio, and automatic transcripts) which was released concurrently with the track. The track generated considerable interest, a‚racted hundreds of new registrations to TREC and fifteen teams, mostly disjoint between search and summarization, made final submissions for assessment. Deep learning was the dominant experimental approach for both search experiments and summarization.

Track coordinator(s):

• Rosie Jones, Spotify Research
• Ben Carterette, Spotify Research
• Ann Clifton, Spotify Research
• Jussi Karlgren, Spotify Research
• Aasish Pappu, Spotify Research
• Sravana Reddy, Spotify Research
• Yongze Yu, Spotify Research
• Maria Eskevich, CLARIN ERIC
• Gareth J. F. Jones, Dublin City University

Tasks:

• summarization: Summarization
• retrieval: Retrieval

Track Web Page: https://trecpodcasts.github.io/

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