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CS-YODAS: A Mined Dataset of In-the-Wild Code-Switched Speech

Proceedings of the Fifteenth Language Resources and Evaluation Conference (LREC 2026)

DOI:10.63317/3fir5kp98qyt

Abstract

We present CS-YODAS, a Creative Commons dataset of in-the-wild code-switched speech mined from multilingual YouTube data. Code-switching, or the alternation between languages within an utterance or conversation, is common in multilingual settings but remains underrepresented in existing CS speech resources, which are typically small, domain-specific, or artificially constructed. Building on the YODAS corpus, we develop a scalable, human-in-the-loop pipeline for identifying and validating naturally occurring code-switching. The resulting dataset, which totals 313 hrs and spans 7 matrix languages, provides diverse, real-world examples of spontaneous code-switched speech. We further analyze the distribution and characteristics of code-switching in the wild, examining language-pair frequencies and switching patterns, and report baseline results for spoken language identification. We hope that CS-YODAS will encourage broader and more comprehensive research on code-switched speech. Dataset link: https://huggingface.co/datasets/byan/cs-yodas.

Details

Paper ID
lrec2026-main-456
Pages
pp. 5776-5784
BibKey
yan-etal-2026-cs
Editor
N/A
Publisher
European Language Resources Association (ELRA)
ISSN
2522-2686
ISBN
978-2-493814-49-4
Conference
The Fifteenth Language Resources and Evaluation Conference (LREC 2026)
Location
Palma, Mallorca, Spain
Date
11 May 2026 16 May 2026

Authors

  • BY

    Brian Yan

  • QW

    Qingzheng Wang

  • MW

    Matthew Wiesner

  • AD

    Anuj Diwan

  • OI

    Olga Iakovenko

  • AP

    Alex Polok

  • IH

    Injy Hamed

  • SS

    Shuichiro Shimizu

  • IE

    Iris Emerman

  • TH

    Thomas Hain

  • DM

    David R. Mortensen

  • PV

    Peter Viechnicki

  • SW

    Shinji Watanabe

Links