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First Steps in ASR for Cypriot Greek: Challenges and Insights

Paper · 2026 · Vivian Stamou, Spyros Armostis, Antigoni Klimi et al.

Summary

Cypriot Greek is a widely spoken Modern Greek dialect, with over 700,000 speakers, but it has no standard spelling. Its sounds, vocabulary and grammar differ from Standard Modern Greek (SMG) enough that general speech recognizers handle it poorly. The authors present what they describe as the first ASR system for this variety.

They use the Cypriot Greek subset ('el-CY') of Mozilla Common Voice Spontaneous Speech, version 23.0. Native speakers transcribed the recordings, and linguists harmonized the spelling using dialect dictionaries and existing conventions, which add diacritics for sounds missing from SMG. A fixed, rule-based normalization pipeline then reduces irrelevant spelling noise. It maps variants to Cypriot forms rather than SMG ones. CTC forced alignment splits the audio into sentence-level segments.

The team fine-tuned four Whisper sizes and also considered XLSR-53. whisper-large-v3 achieved the lowest WER, 33.93%, compared with 37.85% for whisper-medium. The study suggests that larger models combined with careful orthographic normalization are a workable path to ASR for low-resource dialects.

Key points

  • Data: Common Voice Spontaneous Speech v23.0 'el-CY' contains 1,284 clips from 10 speakers, about 10.92 h in total (10.79 h validated). Eight native speakers transcribed it, and two linguists homogenized the spelling.
  • The normalization pipeline has seven deterministic steps: Unicode NFC and lowercasing, punctuation cleanup, artefact removal, collapsing elongations, polytonic-to-monotonic conversion, Greek–Latin character fixes, and dialect-preserving canonicalization. Comparing original and normalized transcripts gives a WER of 15.8% and a CER of 3.8%.
  • Segmentation used ctc-forced-aligner with the mms-300m-1130 model and produced Kaldi-style outputs. Utterances longer than 30 s were dropped to fit Whisper's input limit.
  • Models: whisper-small, whisper-medium, whisper-large-v3 and whisper-large-v3-turbo were fine-tuned. A Greek-fine-tuned XLSR-53 was also used as a comparison system.
  • Best results: whisper-large-v3 reached a WER of 33.93% and whisper-medium reached 37.85%. The larger model was consistently better.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🎓George Mason UniversityFairfax · United States24 works · 1,288 citations🔬Institute for Language and Speech ProcessingMarousi · Greece7 works · 5,529 citations🔬Athena Research and Innovation Center In Information Communication & Knowledge TechnologiesMarousi · Greece9 works · 3,461 citations🎓University of CyprusNicosia · Cyprus2 works

 Fields, topics and concepts

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Computer Science · 16,667 worksArtificial Intelligence · 16,194 worksArts and Humanities · 16,039 worksLanguage and Linguistics · 15,891 worksSignal Processing · 452 works

🧭 Topics 1Research subjects and languages the work is about.Speech & spoken language · 480 works

Cite

Cite as Vivian Stamou, Spyros Armostis, Antigoni Klimi, Georgios Paraskevopoulos, Vassilis Katsouros and Antonios Anastasopoulos. 2026. First Steps in ASR for Cypriot Greek: Challenges and Insights. Proceedings of the First Workshop on Dialects in NLP –- A Resource Perspective.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.63317/2iznmge7hdtx

@inproceedings{stamou2026first,
  title = {{First Steps in ASR for Cypriot Greek: Challenges and Insights}},
  author = {Vivian Stamou, Spyros Armostis, Antigoni Klimi, Georgios Paraskevopoulos, Vassilis Katsouros and Antonios Anastasopoulos},
  booktitle = {Proceedings of the First Workshop on Dialects in NLP –- A Resource Perspective},
  year = {2026},
  doi = {10.63317/2iznmge7hdtx},
  url = {https://doi.org/10.63317/2iznmge7hdtx}
}

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