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A large-scale corpus of religious radio broadcast transcripts from webstream recordings in the United States

arXiv 2607.26249 ↗First posted 28 Jul 2026cs.CL cs.CY cs.SDcited by 0

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Abstract (arXiv)

Religious radio is a widespread but understudied form of mass communication in the United States, and content-level analysis of it has been constrained by the absence of large-scale transcript data. This Data Descriptor presents a corpus of transcribed English-language religious radio broadcasts captured from live webstreams over a one-month period in July 2025. Fifteen-minute segments were recorded on a rolling schedule from 785 distinct streams, which together rebroadcast the signals of more than two thousand AM and FM stations, yielding over 700,000 recordings and more than 60 million diarized lines of speech. Each recording was transcribed and speaker-diarized with an automated pipeline, and segmented and labeled by programming format and topic using a large language model. The corpus is organized as linked tables of stream metadata, recording metadata, and transcript lines. It supports descriptive study of religious broadcasting across regions and traditions, analysis of how social and political issues are discussed in religious media, and speech-processing research in an underrepresented domain.

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References · 5

  1. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 3,972
  2. 2021VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretationcited by 455
  3. 2023WhisperX: Time-Accurate Speech Transcription of Long-Form Audiocited by 320
  4. 2023Powerset multi-class cross entropy loss for neural speaker diarizationcited by 109
  5. 2019RadioTalk: a large-scale corpus of talk radio transcriptscited by 6

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