1 citations · 2 across the 8 of their papers we have counts for
8 papers · 1 filter
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…
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…
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…
Towards Tailored Recovery of Lexical Diversity in Literary Machine Translation
Esther Ploeger, Huiyuan Lai, Rik van Noord +1
Machine translations are found to be lexically poorer than human translations. The loss of lexical diversity through MT poses an issue in the automatic translation of literature, w…
PMB5: Gaining More Insight into Neural Semantic Parsing with Challenging Benchmarks
Xiao Zhang, Chunliu Wang, Rik van Noord +1
The Parallel Meaning Bank (PMB) serves as a corpus for semantic processing with a focus on semantic parsing and text generation. Currently, we witness an excellent performance of n…
Automatic Discrimination of Human and Neural Machine Translation in Multilingual Scenarios
Malina Chichirau, Rik van Noord, Antonio Toral
We tackle the task of automatically discriminating between human and machine translations. As opposed to most previous work, we perform experiments in a multilingual setting, consi…
Character-level Representations Improve DRS-based Semantic Parsing Even in the Age of BERT
Rik van Noord, Antonio Toral, Johan Bos
We combine character-level and contextual language model representations to improve performance on Discourse Representation Structure parsing. Character representations can easily…
The First Shared Task on Discourse Representation Structure Parsing
Lasha Abzianidze, Rik van Noord, Hessel Haagsma +1
The paper presents the IWCS 2019 shared task on semantic parsing where the goal is to produce Discourse Representation Structures (DRSs) for English sentences. DRSs originate from…