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Transcription Accuracy in the Icelandic Gigaword Corpus: Evaluating Automatic and Manual Annotation

Summary

Sociolinguists increasingly rely on large automatically annotated corpora. But transcripts may not faithfully reflect what speakers actually said, and this source of error is rarely examined. The authors study this for Stylistic Fronting (SF), an optional word-order pattern that signals formal style in Icelandic, using the Icelandic Parliament Corpus within the Icelandic Gigaword Corpus.

They compare two sources of SF data. One is automatic extraction from official transcripts written by parliamentary staff, tagged with ABLTagger 3.0.0, lemmatized with Nefnir, and filtered by a Python script. The other is manual correction made by listening to the original audio recordings, covering 2005–2021 for a balanced sample of 20 MPs.

Staff transcribers frequently insert SF that the speaker never produced, so the automatic data show somewhat higher SF rates than the audio-based coding. Even so, both datasets trace the same changes in SF over 16 years. Transcript-based automatic coding therefore remains a usable basis for studying language change across a speaker's lifespan, provided that its upward bias in SF rates is taken into account.

Key points

  • Data: 37,219 automatically extracted SF-eligible tokens from 20 MPs, of which 25,096 (67.43%) were manually checked against audio. The MPs were balanced by gender (10/10), birth year (1942–1990) and eight political parties.
  • Reliability of manual coding: A doubly coded subsample of 980 tokens reached 99.29% inter-annotator agreement (Cohen's Kappa = 0.96).
  • Transcript–audio mismatches:
    • Transcribers added SF in 2,627 cases.
    • They removed SF in only 142 cases.
    • In 812 cases, rewording created an SF context absent from the speech; these tokens were excluded.
  • Source of bias: The automatic tools themselves showed no errors on this construction (relative clauses with sem). The discrepancy comes from editorial normalization of transcripts toward standard written Icelandic.
  • ASR not used: Earlier work found ASR quality on this corpus too low to avoid manual correction. Audio is only authentic from 2005 onward, since earlier recordings are synthesized from the transcripts.

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

Fields: Linguistics & languages

Cite

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.63317/4f2rpzig5h8p

@inproceedings{mechler2026transcription,
  title = {{Transcription Accuracy in the Icelandic Gigaword Corpus: Evaluating Automatic and Manual Annotation}},
  author = {Mechler, Johanna and Stefánsdóttir, Lilja Björk and Ingason, Anton Karl},
  booktitle = {Proceedings of the Fifteenth Language Resources and Evaluation Conference},
  year = {2026},
  doi = {10.63317/4f2rpzig5h8p},
  url = {https://doi.org/10.63317/4f2rpzig5h8p}
}

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