  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, attracted 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. This paper gives an
overview of the tasks and the results of the participants' experiments. The
track will return to TREC 2021 with the same two tasks, incorporating slight
modifications in response to participant feedback.
