RadioTalk: a large-scale corpus of talk radio transcripts
This provides a new dataset for researchers in NLP and social sciences, but it is incremental as it focuses on data collection rather than novel methods.
The authors introduced RadioTalk, a large-scale corpus of 2.8 billion words from 284,000 hours of automatically transcribed talk radio broadcasts, intended for research in NLP, conversational analysis, and social sciences.
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.