by successfully circumventing GPT-4's safeguard through translating unsafe English inputs into low-resource languages. On the AdvBenchmark, GPT-4 engages with the unsafe translated inputs and provides actionable items that can get the users towards their harmful goals 79% of the time, which is...
Low-resource languages (LRL) with complex morphology are known to be more difficult to translate in an automatic way. Some LRLs are particularly more difficult to translate than others due to the lack of research interest or collaboration. In this article, we experiment with a specific LRL, ...
low-resource-languages focuses this list on a lack of digital resources compared to other, high resourced languages.Tools which are built for these languages are not included (unless relevant for dialects or variants): Arabic, Bulgarian, Catalan, Chinese, Croatian, Czech, Danish, Dutch, English,...
The ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP) publishes high quality original archival papers, survey papers, and technical notes in the areas of computation and processing of information in Asian languages, low-resource languages of Africa, Australasia, Oceania...
“Processing short-message communications in low-resource languages.” The work explores the nature of the variation inherent to short message communications in the majority of the world’s languages, and the extent to which modeling this variation can improve natural language processing systems. It ...
Learning cross-lingual information with multilingual BLSTM for speech synthesis of low-resource languages Bidirectional long short-term memory (BLSTM) based speech synthesis has shown great potential in improving the quality of the synthetic speech. However, fo... Q Yu,L Peng,Z Wu,... - IEEE ...
Recently, very large language models (LLMs) have shown exceptional performance on several English NLP tasks with just in-context learning (ICL), but their utility in other languages is still underexplored. We investigate their effectiveness for NLP tasks in low-resource languages (LRLs), especially...
Recent advancements in large language models (LLMs) have enabled the development of systems capable of generating human-like responses across a wide range of tasks. However, research focus has been primarily on high-resource languages such as English, German, and French, whereas low-resource langua...
Crowdsourcing Speech Data for Low-Resource Languages from Low-Income Workers Basil Abraham, Danish Goel, Divya Siddarth, Kalika Bali, Manu Chopra, Monojit Choudhury, Pratik Joshi, Preethi Jyothi, Sunayana Sitaram, Vivek Seshadri Language Resources and Evaluation Conferenc...
We present a multi-task learning approach that jointly trains three word alignment models over disjoint bitexts of three languages - source, target and pivot. Our approach builds upon model triangulation, following Wang et al., which approximates a source-target model by combining source-pivot and...