Search Results for author:
Found 4 papers, 1 papers with code
A Model of Cross-Lingual Knowledge-Grounded Response Generation for Open-Domain Dialogue Systems
Through experiments with a Korean dialogue system, this paper proves that the performance of a non-English dialogue system can be improved by utilizing English knowledge, highlighting the system uses cross-lingual knowledge.
An Emotion-based Korean Multimodal Empathetic Dialogue System
We propose a Korean multimodal dialogue system targeting emotion-based empathetic dialogues because most research in this field has been conducted in a few languages such as English and Japanese and in certain circumstances.
BPM_MT: Enhanced Backchannel Prediction Model using Multi-Task Learning
Backchannel (BC), a short reaction signal of a listener to a speaker’s utterances, helps to improve the quality of the conversation.
Automatic Gloss-level Data Augmentation for Sign Language Translation
In this study, we present three methods of augmenting sign language text modality data, comprising 3, 052 Gloss-level Korean Sign Language (GKSL) and Word-level Korean Language (WKL) sentence pairs.
