Computer-aided translation (CAT), which leverages the advantages of MT systems to help human translators, attracts the attention of researchers. However, research progress in CAT is slower than in automatic MT. One of the main reasons is that almost no public shared tasks are available for CAT research. The lack of such shared tasks has hindered researchers from making continuous progress in this area. Therefore, PRHLT participates in the organization of a shared task in WMT 2022, to push forward the research on CAT. Generally, the task is called Word-Level AutoCompletion (WLAC), which aims to predict a target word given a source sentence, translation context and a human typed character sequence. WLAC plays an important role in a CAT system in enhancing translation efficiency.
- Lip reading for Spanish in real scenarios (LLEER)
- FAKE news and HATE speech (FAKEnHATE-PdC)
- Malicious Actors Profiling and Detection in Online Social Networks Through Arificial Intelligence (MARTINI)
- Fairness and Transparency for equitable NLP applications in social media – Identifying stereotypes and prejudices and developing equitable systems (FairTransNLP-Stereotypes)