We present uroman, a tool for converting text in myriads of languages and scripts such as
Chinese, Arabic and Cyrillic into a common Latin-script representation. The tool relies on …

Due to climate change and the effects of geopolitical and social challenges like the refugee
crisis in Europe, the world is facing an unprecedented set of humanitarian problems …

In a corruption of John Searle's famous AI thought experiment, the Chinese Room (Searle,
1980), we twist its original intent by enabling humans to translate text, eg from Uyghur to …

In low-resource natural language processing (NLP), the key problems are a lack of target
language training data, and a lack of native speakers to create it. Cross-lingual methods …

In the age of information overload, the ability to automatically extract useful structured
information from texts is urgently needed by a wide range of applications, such as …

During the course of a Humanitarian Assistance-Disaster Relief (HADR) crisis, that can
happen anywhere in the world, real-time information is often posted online by the people in …

This paper describes a novel approach of multitask learning for an end-to-end optimization
technique for document classification. The application motivation comes from the need to …

Humanitarian and geopolitical crises (such as COVID-19) are frequently extra-national in
scope. Technology, including applications of natural language processing and machine …

Extracting information from natural language text is one of the most challenging and long-
standing problems in the field of Natural Language Processing (NLP). Information Extraction …