WavePulse: Real-time Content Analytics of Radio Livestreams
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Abstract (arXiv)
Radio remains a pervasive medium for mass information dissemination, with AM/FM stations reaching more Americans than either smartphone-based social networking or live television. Increasingly, radio broadcasts are also streamed online and accessed over the Internet. We present WavePulse, a framework that records, documents, and analyzes radio content in real-time. While our framework is generally applicable, we showcase the efficacy of WavePulse in a collaborative project with a team of political scientists focusing on the 2024 Presidential Elections. We use WavePulse to monitor livestreams of 396 news radio stations over a period of three months, processing close to 500,000 hours of audio streams. These streams were converted into time-stamped, diarized transcripts and analyzed to track answer key political science questions at both the national and state levels. Our analysis revealed how local issues interacted with national trends, providing insights into information flow. Our results demonstrate WavePulse's efficacy in capturing and analyzing content from radio livestreams sourced from the Web. Code and dataset can be accessed at urlhttps://wave-pulse.io.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 34 references that are in the map. First posted on arXiv 23 Dec 2024.
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References · 7
- 2024The Llama 3 Herd of Modelscited by 14,715
- 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 4,057
- 2023WhisperX: Time-Accurate Speech Transcription of Long-Form Audiocited by 326
- 2023Fast Conformer with Linearly Scalable Attention for Efficient Speech Recognitioncited by 124
- 2023Powerset multi-class cross entropy loss for neural speaker diarizationcited by 111
- 2022TweetNLP: Cutting-Edge Natural Language Processing for Social Mediacited by 71
- 2019RadioTalk: a large-scale corpus of talk radio transcriptscited by 6
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