Machine Translation
Machine translation (MT) aims to automatically translate text between languages, with current research heavily focused on leveraging large language models (LLMs) and exploring various architectures like encoder-decoder and decoder-only models. Key areas of investigation include improving translation quality, particularly for low-resource languages and specialized domains like medicine, mitigating biases (e.g., gender bias), and enhancing evaluation methods beyond simple correlation with human judgments. These advancements have significant implications for cross-cultural communication, information access, and the development of more equitable and effective multilingual technologies.
Papers
VAKTA-SETU: A Speech-to-Speech Machine Translation Service in Select Indic Languages
Shivam Mhaskar, Vineet Bhat, Akshay Batheja, Sourabh Deoghare, Paramveer Choudhary, Pushpak Bhattacharyya
Is Translation Helpful? An Empirical Analysis of Cross-Lingual Transfer in Low-Resource Dialog Generation
Lei Shen, Shuai Yu, Xiaoyu Shen
Machine Translation by Projecting Text into the Same Phonetic-Orthographic Space Using a Common Encoding
Amit Kumar, Shantipriya Parida, Ajay Pratap, Anil Kumar Singh
The Inside Story: Towards Better Understanding of Machine Translation Neural Evaluation Metrics
Ricardo Rei, Nuno M. Guerreiro, Marcos Treviso, Luisa Coheur, Alon Lavie, André F. T. Martins
ReSeTOX: Re-learning attention weights for toxicity mitigation in machine translation
Javier García Gilabert, Carlos Escolano, Marta R. Costa-Jussà
HalOmi: A Manually Annotated Benchmark for Multilingual Hallucination and Omission Detection in Machine Translation
David Dale, Elena Voita, Janice Lam, Prangthip Hansanti, Christophe Ropers, Elahe Kalbassi, Cynthia Gao, Loïc Barrault, Marta R. Costa-jussà
DUB: Discrete Unit Back-translation for Speech Translation
Dong Zhang, Rong Ye, Tom Ko, Mingxuan Wang, Yaqian Zhou
Discourse Centric Evaluation of Machine Translation with a Densely Annotated Parallel Corpus
Yuchen Eleanor Jiang, Tianyu Liu, Shuming Ma, Dongdong Zhang, Mrinmaya Sachan, Ryan Cotterell
NollySenti: Leveraging Transfer Learning and Machine Translation for Nigerian Movie Sentiment Classification
Iyanuoluwa Shode, David Ifeoluwa Adelani, Jing Peng, Anna Feldman
Deep Learning Methods for Extracting Metaphorical Names of Flowers and Plants
Amal Haddad Haddad, Damith Premasiri, Tharindu Ranasinghe, Ruslan Mitkov
Bring More Attention to Syntactic Symmetry for Automatic Postediting of High-Quality Machine Translations
Baikjin Jung, Myungji Lee, Jong-Hyeok Lee, Yunsu Kim
ChatGPT Perpetuates Gender Bias in Machine Translation and Ignores Non-Gendered Pronouns: Findings across Bengali and Five other Low-Resource Languages
Sourojit Ghosh, Aylin Caliskan
Accelerating Transformer Inference for Translation via Parallel Decoding
Andrea Santilli, Silvio Severino, Emilian Postolache, Valentino Maiorca, Michele Mancusi, Riccardo Marin, Emanuele Rodolà
A Survey on Zero Pronoun Translation
Longyue Wang, Siyou Liu, Mingzhou Xu, Linfeng Song, Shuming Shi, Zhaopeng Tu
"I'm fully who I am": Towards Centering Transgender and Non-Binary Voices to Measure Biases in Open Language Generation
Anaelia Ovalle, Palash Goyal, Jwala Dhamala, Zachary Jaggers, Kai-Wei Chang, Aram Galstyan, Richard Zemel, Rahul Gupta
Epsilon Sampling Rocks: Investigating Sampling Strategies for Minimum Bayes Risk Decoding for Machine Translation
Markus Freitag, Behrooz Ghorbani, Patrick Fernandes