Lexicography Saves Lives (LSL): Automatically Translating Suicide-Related Language
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866913620774879232 |
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| author | Schoene, Annika Marie Ortega, John E. Zevallos, Rodolfo Joel Ihle, Laura Haaber |
| author_facet | Schoene, Annika Marie Ortega, John E. Zevallos, Rodolfo Joel Ihle, Laura Haaber |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2412_15497 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Lexicography Saves Lives (LSL): Automatically Translating Suicide-Related Language Schoene, Annika Marie Ortega, John E. Zevallos, Rodolfo Joel Ihle, Laura Haaber Computation and Language Artificial Intelligence 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. |
| title | Lexicography Saves Lives (LSL): Automatically Translating Suicide-Related Language |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2412.15497 |