3 papers
cs.CL2026
Can Large Language Models Reliably Correct Errors in Low-Resource ASR? A Contamination-Aware Case Study on West Frisian
Yun Hao, Reihaneh Amooie, Wietse de Vries +2
Automatic speech recognition (ASR) has improved substantially in recent years, yet performance remains limited for low-resource languages. Large language models (LLMs) have shown p…
cs.CL2026
Creativity Bias: How Machine Evaluation Struggles with Creativity in Literary Translations
Kyo Gerrits, Rik van Noord, Ana Guerberof Arenas
This article investigates the performance of automatic evaluation metrics (AEMs) and LLM-as-a-judge evaluation on literary translation across multiple languages, genres, and transl…
cs.CL2025
Multi-perspective Alignment for Increasing Naturalness in Neural Machine Translation
Huiyuan Lai, Esther Ploeger, Rik van Noord +1
Neural machine translation (NMT) systems amplify lexical biases present in their training data, leading to artificially impoverished language in output translations. These language…