Chenhui Chu

A Brief Survey of Multilingual Neural Machine Translation

2019 · arXiv (Cornell University)

We present a survey on multilingual neural machine translation (MNMT), which has gained a lot of traction in the recent years. MNMT has been useful in improving translation quality as a result of knowledge transfer. …

KyotoMOS: An Automatic MOS Scoring System for Speech Synthesis

2023

The Mean Opinion Score (MOS) serves as a subjective measure for assessing the quality of synthesized speech. Nevertheless, the conventional approach to MOS evaluations can be resource-intensive in terms of both time and cost. This …

EMS: Efficient and Effective Massively Multilingual Sentence Embedding Learning

2024 · IEEE/ACM Transactions on Audio Speech and Language Processing

Massively multilingual sentence representation models, e.g., LASER, SBERT-distill, and LaBSE, help significantly improve cross-lingual downstream tasks. However, the use of a large amount of data or inefficient model architectures results in heavy computation to train …

StyEmp: Stylizing Empathetic Response Generation via Multi-Grained Prefix Encoder and Personality Reinforcement

2024 · arXiv (Cornell University)

Recent approaches for empathetic response generation mainly focus on emotional resonance and user understanding, without considering the system's personality. Consistent personality is evident in real human expression and is important for creating trustworthy systems. To …

An Empirical Comparison of Simple Domain Adaptation Methods for Neural Machine Translation

2017 · arXiv (Cornell University)

In this paper, we propose a novel domain adaptation method named "mixed fine tuning" for neural machine translation (NMT). We combine two existing approaches namely fine tuning and multi domain NMT. We first train an …

An Empirical Comparison of Domain Adaptation Methods for Neural Machine Translation

2017

In this paper, we propose a novel domain adaptation method named "mixed fine tuning" for neural machine translation (NMT). We combine two existing approaches namely fine tuning and multi domain NMT. We first train an …

Overview of the 8th Workshop on Asian Translation

2021

Toshiaki Nakazawa, Hideki Nakayama, Chenchen Ding, Raj Dabre, Shohei Higashiyama, Hideya Mino, Isao Goto, Win Pa Pa, Anoop Kunchukuttan, Shantipriya Parida, Ondřej Bojar, Chenhui Chu, Akiko Eriguchi, Kaori Abe, Yusuke Oda, Sadao Kurohashi. Proceedings of …

A Survey of Domain Adaptation for Neural Machine Translation

2018 · arXiv (Cornell University)

Neural machine translation (NMT) is a deep learning based approach for machine translation, which yields the state-of-the-art translation performance in scenarios where large-scale parallel corpora are available. Although the high-quality and domain-specific translation is crucial …