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Found 13 papers, 0 papers with code
The Contribution of Lyrics and Acoustics to Collaborative Understanding of Mood
We find that a pretrained transformer-based language model in a zero-shot setting -- i. e., out of the box with no further training on our data -- is powerful for capturing song-mood associations.
Podcast Metadata and Content: Episode Relevance andAttractiveness in Ad Hoc Search
We describe a set of diverse podcast information needs and different approaches to assessing retrieved content for relevance.
Current Challenges and Future Directions in Podcast Information Access
Podcasts are spoken documents across a wide-range of genres and styles, with growing listenership across the world, and a rapidly lowering barrier to entry for both listeners and creators.
Modeling Language Usage and Listener Engagement in Podcasts
While there is an abundance of popular writing targeted to podcast creators on how to speak in ways that engage their listeners, there has been little data-driven analysis of podcasts that relates linguistic style with listener engagement.
Spotify at TREC 2020: Genre-Aware Abstractive Podcast Summarization
This paper contains the description of our submissions to the summarization task of the Podcast Track in TREC (the Text REtrieval Conference) 2020.
TREC 2020 Podcasts Track Overview
The Podcast Track is new at the Text Retrieval Conference (TREC) in 2020.
Detecting Extraneous Content in Podcasts
Podcast episodes often contain material extraneous to the main content, such as advertisements, interleaved within the audio and the written descriptions.
100,000 Podcasts: A Spoken English Document Corpus
Paired with the audio files, they are also a resource for speech processing and the study of paralinguistic, sociolinguistic, and acoustic aspects of the domain.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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