The Spoken Wikipedia Presentation Corpus
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Electrical Engineering and Systems Science > Audio and Speech Processing
arXiv:2609.21676 (eess)
[Submitted on 18 Sep 2026]
Title:The Spoken Wikipedia Presentation Corpus
View a PDF of the paper titled The Spoken Wikipedia Presentation Corpus, by Thomas Ranzenberger and 3 other authors
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Abstract:We present the Spoken Wikipedia Presentation Corpus, an extension of the Spoken Wikipedia Corpora featuring LLM-generated slide decks for multimodal ASR. Slides are created from LLM-segmented sections using a hybrid pipeline that combines LLM-based content planning with rule-based design decisions. For each section, an LLM generates a slide title, bullet points, a takeaway message, and a visual description that is used to create an illustration. Rule-based matching then selects layouts, themes, and styles to produce the final slides. A vision LLM extracts slide text as Markdown. We evaluate multiple ASR and spoken language models (SLMs). The best model achieves an average micro-WER of 10.23% and an average micro-CER of 6.48% on audio-only inputs. English yields the lowest error rates, followed by German and Dutch, while performance declines across lower-resource languages. Although audio-only baselines are strong, multimodal zero-shot prompting of omni models remains challenging. The aligned slide, text, and audio data show a strong potential to improve recognition through cross-modal context.
| Comments: | Accepted at SLT 2026 |
| Subjects: | Audio and Speech Processing (eess.AS); Computation and Language (cs.CL); Multimedia (cs.MM); Sound (cs.SD) |
| Cite as: | arXiv:2609.21676 [eess.AS] |
| (or arXiv:2609.21676v1 [eess.AS] for this version) | |
| https://doi.org/10.48550/arXiv.2609.21676
arXiv-issued DOI via DataCite (pending registration)
|
Submission history
From: Thomas Ranzenberger [view email][v1] Fri, 18 Sep 2026 12:13:06 UTC (306 KB)
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