mlsanityData to 14 Oct 2026

Introducing MELI: the Mandarin-English Language Interview Corpus

arXiv 2603.27043 ↗First posted 27 Mar 2026cs.CLcited by 0

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Abstract (arXiv)

We introduce the Mandarin-English Language Interview (MELI) Corpus, an open-source resource of 29.8 hours of speech from 51 Mandarin-English bilingual speakers. MELI combines matched sessions in Mandarin and English with two speaking styles: read sentences and spontaneous interviews about language varieties, standardness, and learning experiences. Audio was recorded at 44.1 kHz (16-bit, stereo). Interviews were fully transcribed, force-aligned at word and phone levels, and anonymized. Descriptively, the Mandarin component totals ~14.7 hours (mean duration 17.3 minutes) and the English component ~15.1 hours (mean duration 17.8 minutes). We report token/type statistics for each language and document code-switching patterns (frequent in Mandarin sessions; more limited in English sessions). The corpus design supports within-/cross-speaker, within/cross-language acoustic comparison and links acoustics to speakers' stated language attitudes, enabling both quantitative and qualitative analyses. The MELI Corpus will be released with transcriptions, alignments, metadata, scans of labelled maps and documentation under a CC BY-NC 4.0 license.

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References · 7

  1. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 4,057
  2. 2017AISHELL-1: An Open-Source Mandarin Speech Corpus and A Speech Recognition Baselinecited by 373
  3. 2021WenetSpeech: A 10000+ Hours Multi-domain Mandarin Corpus for Speech Recognitioncited by 197
  4. 2021ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversationcited by 44
  5. 2015THCHS-30 : A Free Chinese Speech Corpuscited by 43
  6. 2022Open Source MagicData-RAMC: A Rich Annotated Mandarin Conversational(RAMC) Speech Datasetcited by 40
  7. 2022TALCS: An Open-Source Mandarin-English Code-Switching Corpus and a Speech Recognition Baselinecited by 17

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