arXiv:2605.26891v1 Announce Type: new Abstract: This paper presents a multilingual customer service self-help corpus comprising 1,122 manually validated documents in Finnish, Danish, Norwegian, and Swedish, totaling over one million tokens. The documents have been sourced from the public self-help pages of four Nordic telecommunications operators and subsequently filtered for person-identifiable information and relevance through a combined LLM and human annotation pipeline. Domain-specific datasets for Nordic languages remain scarce, particularly in customer service: a domain of growing import
The increasing demand for localized and domain-specific large language models for customer service in non-English markets is driving the creation of such datasets.
This development addresses a critical scarcity of Nordic language datasets for AI, which is essential for developing effective, localized AI solutions and reducing dependency on models trained primarily on English data.
The availability of this corpus facilitates the training of better-performing LLMs for customer service in Nordic languages, potentially leading to improved automation and more efficient operations for telecommunications companies in the region.
- · Nordic telecommunications operators
- · Nordic language AI developers
- · Nordic consumers
- · Companies relying solely on English-centric AI models in Nordic markets
Improved customer service AI across Nordic languages through better-trained models.
Accelerated development of other domain-specific AI applications in Nordic languages due to methodological precedent and data availability.
Increased competitiveness of Nordic AI enterprises in localized service solutions, potentially leading to regional AI hubs.
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Read at arXiv cs.CL