no code implementations • 26 Jan 2024 • Seonmin Koo, Chanjun Park, Jinsung Kim, Jaehyung Seo, Sugyeong Eo, Hyeonseok Moon, Heuiseok Lim
To effectively address this, it is imperative to consider both the speech-level, crucial for recognition accuracy, and the text-level, critical for user-friendliness.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
1 code implementation • 11 Jun 2023 • Sugyeong Eo, Hyeonseok Moon, Jinsung Kim, Yuna Hur, Jeongwook Kim, Songeun Lee, Changwoo Chun, Sungsoo Park, Heuiseok Lim
In this paper, we propose a QAG framework that enhances QA type diversity by producing different interrogative sentences and implicit/explicit answers.
1 code implementation • 6 Jan 2023 • Jungwoo Lim, Myunghoon Kang, Yuna Hur, SeungWon Jung, Jinsung Kim, Yoonna Jang, Dongyub Lee, Hyesung Ji, Donghoon Shin, Seungryong Kim, Heuiseok Lim
The agent selects the proper knowledge and persona to use for generating the answers with our candidate scoring implemented with a poly-encoder.
1 code implementation • COLING 2022 • Gyeongmin Kim, Jinsung Kim, Junyoung Son, Heuiseok Lim
As digitized traditional cultural heritage documents have rapidly increased, resulting in an increased need for preservation and management, practical recognition of entities and typification of their classes has become essential.
1 code implementation • COLING 2022 • Junyoung Son, Jinsung Kim, Jungwoo Lim, Heuiseok Lim
To effectively exploit inherent knowledge of PLMs without extra layers and consider scattered semantic cues on the relation between the arguments, we propose a Guiding model with RelAtional Semantics using Prompt (GRASP).
Ranked #2 on Dialog Relation Extraction on DialogRE
Dialog Relation Extraction Emotion Recognition in Conversation +1
no code implementations • 26 Nov 2021 • Jinsung Kim, Yeong-Seok Jeong, Woosung Choi, Jaehwa Chung, Soonyoung Jung
To address this issue, we propose a novel method to learn source-awarelatent representations of music through Vector-Quantized Variational Auto-Encoder(VQ-VAE). We train our VQ-VAE to encode an input mixture into a tensor of integers in a discrete latentspace, and design them to have a decomposed structure which allows humans to manipulatethe latent vector in a source-aware manner.
no code implementations • 24 Nov 2021 • Yeong-Seok Jeong, Jinsung Kim, Woosung Choi, Jaehwa Chung, Soonyoung Jung
Conditioned source separations have attracted significant attention because of their flexibility, applicability and extensionality.