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arXiv:1907.07073cs.CL

RadioTalk: a large-scale corpus of talk radio transcripts

Doug Beeferman, William Brannon, Deb Roy

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Abstract

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.

arXiv comments
5 pages, 4 figures, accepted by Interspeech 2019
Journal reference
Proc. Interspeech 2019, 564-568 (2019)
DOI
doi:10.21437/Interspeech.2019-2714
Subjects
cs.CLComputation and Language

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  1. Online speech recognition with wav2letter anywhere 1 comment

    • Earlier this year the Media Lab did an absolutely ginormous automated transcription project. Off the top of my head, it was ~2.8 billion words. 13.1% error rate (vs. ~7% error rate for Google's proprietary solution). Found the paper on it: https://arxiv.org/pdf/1907.07073.pdf

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