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RadioTalk: a large-scale corpus of talk radio transcripts

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arxiv 1907.07073 v1 pith:45X5I7DE submitted 2019-07-16 cs.CL

classification cs.CL
keywords corpusradiospeechradiotalktalktranscriptsanalysesanalysis
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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.

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  1. Toxicity Begets Toxicity: Unraveling Conversational Chains in Political Podcasts

    cs.CL 2025-01 conditional novelty 6.0 of 10

    Political podcast toxic segments tend to be longer, more repetitive, more figurative, and angrier than neighboring talk, but some of that pattern is a side effect of how segments were defined.

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