RadioTalk: a large-scale corpus of talk radio transcripts
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Abstract (arXiv)
We introduce RadioTalk, a corpus of speech recognition transcripts sampled from talk radio broadcasts in the United States between October of 2018 and March of 2019. The corpus is intended for use by researchers in the fields of natural language processing, conversational analysis, and the social sciences. The corpus encompasses approximately 2.8 billion words of automatically transcribed speech from 284,000 hours of radio, together with metadata about the speech, such as geographical location, speaker turn boundaries, gender, and radio program information. In this paper we summarize why and how we prepared the corpus, give some descriptive statistics on stations, shows and speakers, and carry out a few high-level analyses.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 16 Jul 2019.
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Citing papers per year: 2021: 2; 2022: 0; 2023: 0; 2024: 2; 2025: 1; 2026: 1.
6 papers.
- 2021Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Surveycited by 130
- 2021Using Radio Archives for Low-Resource Speech Recognition: Towards an Intelligent Virtual Assistant for Illiterate Userscited by 16
- 2025Toxicity Begets Toxicity: Unraveling Conversational Chains in Political Podcastscited by 4
- 2024News Reporter: A Multi-lingual LLM Framework for Broadcast T.V Newscited by 0
- 2024WavePulse: Real-time Content Analytics of Radio Livestreamscited by 0
- 2026A large-scale corpus of religious radio broadcast transcripts from webstream recordings in the United Statescited by 0
- 2026A large-scale corpus of religious radio broadcast transcripts from webstream recordings in the United States28 Jul 2026
- 2025Toxicity Begets Toxicity: Unraveling Conversational Chains in Political Podcasts22 Jan 2025
- 2024WavePulse: Real-time Content Analytics of Radio Livestreams23 Dec 2024
- 2024News Reporter: A Multi-lingual LLM Framework for Broadcast T.V News10 Oct 2024
- 2021Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Survey10 May 2021
- 2021Using Radio Archives for Low-Resource Speech Recognition: Towards an Intelligent Virtual Assistant for Illiterate Users27 Apr 2021