The Spotify Podcast Dataset
This dataset addresses a gap for IR and NLP researchers studying podcasts, which are a growing but understudied audio medium, though it is incremental as it primarily provides new data rather than novel methods.
The authors tackled the lack of large-scale datasets for podcast research by creating the Spotify Podcast Dataset, which includes approximately 100K podcast episodes with raw audio and ASR transcripts, totaling over 47,000 hours of transcribed audio and being an order of magnitude larger than previous corpora.
Podcasts are a relatively new form of audio media. Episodes appear on a regular cadence, and come in many different formats and levels of formality. They can be formal news journalism or conversational chat; fiction or non-fiction. They are rapidly growing in popularity and yet have been relatively little studied. As an audio format, podcasts are more varied in style and production types than, say, broadcast news, and contain many more genres than typically studied in video research. The medium is therefore a rich domain with many research avenues for the IR and NLP communities. We present the Spotify Podcast Dataset, a set of approximately 100K podcast episodes comprised of raw audio files along with accompanying ASR transcripts. This represents over 47,000 hours of transcribed audio, and is an order of magnitude larger than previous speech-to-text corpora.