@inproceedings{konstantinidou-etal-2026-speech,
    title = "A Speech Resource for the {P}ontic {G}reek Dialect: Transcription Choices and Baseline {ASR} Evaluation",
    author = "Konstantinidou, Rodanna  and
      Tsoukala, Chara  and
      Stamou, Vivian  and
      Giouli, Voula  and
      Markantonatou, Stella",
    editor = "Anastasopoulos, Antonis  and
      Markantonatou, Stella  and
      Ralli, Angela  and
      Zampieri, Marcos  and
      Bompolas, Stavros  and
      Stamou, Vivian",
    booktitle = "Proceedings of the First Workshop on Dialects in {NLP} {---} A Resource Perspective",
    month = may,
    year = "2026",
    address = "Palma de Mallorca",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/test-year-match/2026.dialres-1.29/",
    doi = "10.63317/3rq2murx2626",
    pages = "300--307",
    abstract = "Pontic Greek is a living but endangered Modern Greek dialect that lacks publicly available AI-oriented speech resources and ASR benchmarks. This work reports on the first systematic inference-only (zero-shot) ASR evaluation on authentic Pontic speech. Progress on Pontic ASR is hindered by two coupled challenges: the scarcity of transcribed speech data and the absence of a standardized orthography, which makes it difficult to create consistent reference transcriptions for evaluation. We address these challenges by releasing a new speech corpus of contemporary Pontic as spoken in Northern Greece, derived from natural conversations and provided with manual, utterance-level, time-aligned transcriptions. To reduce annotator bias and increase practical usability, we collect community evidence on written-form preferences via a small questionnaire and use the observed patterns to guide a consistent Greek-script transcription scheme. We use this corpus to perform inference-only (zero-shot) ASR evaluation, benchmarking four state-of-the-art pretrained speech recognition models under a unified evaluation protocol. Results show that zero-shot recognition remains challenging, establishing baseline figures and underscoring the need for dialect-specific data and adaptation."
}