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| Main Author: | |
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| Format: | Recurso digital |
| Language: | English |
| Published: |
Zenodo
2025
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| Subjects: | |
| Online Access: | https://doi.org/10.5281/zenodo.17855229 |
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- <p><strong>Description:</strong></p> <p>This dataset provides bag-of-words (BOW) representations of podcast transcripts derived from a large-scale corpus of English-language podcasts. The corpus spans all 19 Apple Podcasts genres and includes over 15,000 episodes from approximately 1,900 shows.</p> <p>Transcripts were generated using Hugging Face's Distil-Whisper-Large-v3 automatic speech recognition model. Text is lowercased but otherwise unprocessed.</p> <p> </p> <p><strong>Files:</strong></p> <ul> <li><code>bow_matrix.npz</code> — Sparse bag-of-words matrix (scipy sparse format, documents × terms)</li> <li><code>metadata.csv</code> — Podcast title, episode title, and description for each document (row indices correspond to matrix rows)</li> <li><code>vocabulary.csv</code> — Terms in the vocabulary (column indices correspond to matrix</li> </ul> <p> </p> <p><strong>Usage:</strong></p> <div> <div> <div> <div> </div> </div> </div> <div> <pre><code><span>from</span> scipy <span>import</span> sparse <span>import</span> pandas <span>as</span> pd bow_matrix <span>=</span> sparse<span>.</span>load_npz<span>(</span><span>'bow_matrix.npz'</span><span>)</span> metadata <span>=</span> pd<span>.</span>read_csv<span>(</span><span>'metadata.csv'</span><span>)</span> vocabulary <span>=</span> pd<span>.</span>read_csv<span>(</span><span>'vocabulary.csv'</span><span>)</span><span>[</span><span>'term'</span><span>]</span><span>.</span>tolist<span>(</span><span>)<br><br></span></code></pre> <p><strong>Related publication:</strong></p> <p>For a detailed description of the data collection and transcription process, see:</p> <p>Verreyen, L. (2025). Podcasts as Data: Building a Dataset for Large-Scale Audio Content Analysis. In T. Arnold, M. Fantoli, & R. Ros (Eds.), <em>Computational Humanities Research 2025</em> (Vol. 3, pp. 231–248). Anthology of Computers and the Humanities. <a href="https://doi.org/10.63744/QgeF94c0fP7D">https://doi.org/10.63744/QgeF94c0fP7D</a></p> <pre> </pre> <pre> </pre> <pre> </pre> </div> </div>