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The Spoken Wikipedia Corpus collection: Harvesting, alignment and an application to hyperlistening

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Abstract

Spoken corpora are important for speech research, but are expensive to create and do not necessarily reflect (read or spontaneous) speech ‘in the wild’. We report on our conversion of the preexisting and freely available Spoken Wikipedia into a speech resource. The Spoken Wikipedia project unites volunteer readers of Wikipedia articles. There are initiatives to create and sustain Spoken Wikipedia versions in many languages and hence the available data grows over time. Thousands of spoken articles are available to users who prefer a spoken over the written version. We turn these semi-structured collections into structured and time-aligned corpora, keeping the exact correspondence with the original hypertext as well as all available metadata. Thus, we make the Spoken Wikipedia accessible for sustainable research. We present our open-source software pipeline that downloads, extracts, normalizes and text–speech aligns the Spoken Wikipedia. Additional language versions can be exploited by adapting configuration files or extending the software if necessary for language peculiarities. We also present and analyze the resulting corpora for German, English, and Dutch, which presently total 1005 h and grow at an estimated 87 h per year. The corpora, together with our software, are available via http://islrn.org/resources/684-927-624-257-3/. As a prototype usage of the time-aligned corpus, we describe an experiment about the preferred modalities for interacting with information-rich read-out hypertext. We find alignments to help improve user experience and factual information access by enabling targeted interaction.

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Notes

  1. http://www.voxforge.org.

  2. http://en.wikipedia.org/wiki/Wikipedia:WikiProject_Spoken_Wikipedia; also contains links to other languages. Please note that the authors are not involved in that project.

  3. http://www.alexa.com/topsites.

  4. https://en.wikipedia.org/wiki/File:Spoken_Wikipedia_Benefits.jpg.

  5. https://en.wikipedia.org/wiki/Wikipedia:Manual_of_Style/Layout.

  6. We want to point out that Wikipedia itself does not offer such statistics (beyond the number of articles in the category) but that such statistics can be easily created with the software described in Sect. 3.

  7. We have not manually checked yet whether that speaker may have also edited other speaker’s work and uploaded this under one unifying name.

  8. English articles can be distinguished as either ‘good’ or ‘featured’, where the corresponding German categories are ‘lesenswert’ (worth reading) and ‘exzellent’.

  9. As can be seen in the graph, there are some growth spurts that were introduced by concerted efforts (in particular for Dutch). While these equal out over time for large languages, the future growth for Dutch is unpredictable at this time.

  10. Unlike the total number of articles, which appears to saturate, the raw data contained in Wikipedia still grows linearly: https://commons.wikimedia.org/w/index.php?title=File:Wikipedia_article_size_in_gigabytes.png&oldid=243766150.

  11. One might argue about the correctness of tokenization or appropriateness of linking. However, such theoretical considerations do not solve the problems associated with using preexisting data and tools.

  12. https://github.com/wiseman/py-webrtcvad, we report mean results of settings ‘1’ and ‘2’.

  13. Our implementation is available at http://github.com/hainoon/wikipediareader.

  14. https://cloud.google.com/speech/.

  15. http://www.pediaphon.org.

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Acknowledgements

We would like to thank all Wikipedia authors and speakers for creating this tremendous amount of data. We thank Florian Stegen for designing the initial version of the corpus extraction and alignment software that we built on. We also thank Marcel Rohde for running the experiment and collaborating on the initial workshop publication of the Spoken Wikipedia browser.

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Authors and Affiliations

  1. School of Computer Science, Language Technology Institute, Carnegie Mellon University, 5000 Forbes Ave, Pittsburgh, PA, 15213, USA

    Timo Baumann

  2. FB Informatik, Natural Language Systems group, Universität Hamburg, Vogt-Kölln-Straße 30, 22527, Hamburg, Germany

    Arne Köhn & Felix Hennig

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  1. Timo Baumann
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Correspondence to Timo Baumann.

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This article extends and consolidates previous research (Köhn et al. 2016; Rohde and Baumann 2016). This work was partly supported by a PostDoc grant by Daimler-and-Benz-foundation to the first author.

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Baumann, T., Köhn, A. & Hennig, F. The Spoken Wikipedia Corpus collection: Harvesting, alignment and an application to hyperlistening. Lang Resources & Evaluation 53, 303–329 (2019). https://doi.org/10.1007/s10579-017-9410-y

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