4 papers
Automatically Generating Chinese Homophone Words to Probe Machine Translation Estimation Systems
Shenbin Qian, Constantin OrÄsan, Diptesh Kanojia +1
Evaluating machine translation (MT) of user-generated content (UGC) involves unique challenges such as checking whether the nuance of emotions from the source are preserved in the…
Are Large Language Models State-of-the-art Quality Estimators for Machine Translation of User-generated Content?
Shenbin Qian, Constantin OrÄsan, Diptesh Kanojia +1
This paper investigates whether large language models (LLMs) are state-of-the-art quality estimators for machine translation of user-generated content (UGC) that contains emotional…
Edit Distances and Their Applications to Downstream Tasks in Research and Commercial Contexts
Félix do Carmo, Diptesh Kanojia
The tutorial describes the concept of edit distances applied to research and commercial contexts. We use Translation Edit Rate (TER), Levenshtein, Damerau-Levenshtein, Longest Comm…
A Multi-task Learning Framework for Evaluating Machine Translation of Emotion-loaded User-generated Content
Shenbin Qian, Constantin OrÄsan, Diptesh Kanojia +1
Machine translation (MT) of user-generated content (UGC) poses unique challenges, including handling slang, emotion, and literary devices like irony and sarcasm. Evaluating the qua…