CLAIDec 20, 2024

Lexicography Saves Lives (LSL): Automatically Translating Suicide-Related Language

arXiv:2412.15497v121 citationsh-index: 2
Originality Synthesis-oriented
AI Analysis

This addresses a global public health issue by enabling better suicide risk detection across diverse cultures, though it is incremental as it builds on existing dictionaries.

The paper tackles the lack of suicide-related language resources in non-English languages by translating a dictionary into 200 languages and providing ethical guidelines, with human evaluations conducted on a subset.

Recent years have seen a marked increase in research that aims to identify or predict risk, intention or ideation of suicide. The majority of new tasks, datasets, language models and other resources focus on English and on suicide in the context of Western culture. However, suicide is global issue and reducing suicide rate by 2030 is one of the key goals of the UN's Sustainable Development Goals. Previous work has used English dictionaries related to suicide to translate into different target languages due to lack of other available resources. Naturally, this leads to a variety of ethical tensions (e.g.: linguistic misrepresentation), where discourse around suicide is not present in a particular culture or country. In this work, we introduce the 'Lexicography Saves Lives Project' to address this issue and make three distinct contributions. First, we outline ethical consideration and provide overview guidelines to mitigate harm in developing suicide-related resources. Next, we translate an existing dictionary related to suicidal ideation into 200 different languages and conduct human evaluations on a subset of translated dictionaries. Finally, we introduce a public website to make our resources available and enable community participation.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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