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Lombard language corpora suffer from data quality and bias issues

By PulseAugur Editorial · [2 sources] ·

Researchers have audited text corpora for the Lombard language, revealing significant issues with data quality and representation. Despite the appearance of abundant web-scraped data, many datasets suffer from misidentification, boilerplate text, and non-linguistic noise. The analysis also highlighted a severe bias towards Western Lombard varieties, marginalizing Eastern ones and indicating a need for community-driven, variety-aware data curation over simple quantity-based scraping. AI

IMPACT Highlights critical data quality and representation challenges for under-resourced languages, impacting NLP model development.

RANK_REASON The cluster contains an academic paper detailing research findings on language corpora.

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Edoardo Signoroni, Pavel Rychl\'y ·

    "Chi nas dal soch el sent de legn" -- Auditing Text Corpora for Lombard

    arXiv:2606.06349v1 Announce Type: new Abstract: Several of the world's languages are still under-resourced in terms of Natural Language Processing (NLP) tools. This is mostly due to the lack of high-quality datasets to train, develop, and evaluate systems and models for several t…

  2. arXiv cs.CL TIER_1 English(EN) · Pavel Rychlý ·

    "Chi nas dal soch el sent de legn" -- Auditing Text Corpora for Lombard

    Several of the world's languages are still under-resourced in terms of Natural Language Processing (NLP) tools. This is mostly due to the lack of high-quality datasets to train, develop, and evaluate systems and models for several tasks, such as Machine Translation (MT). We condu…

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