Search Results for author: Jaeyeon Lee

Found 8 papers, 4 papers with code

VOTE400(Voide Of The Elderly 400 Hours): A Speech Dataset to Study Voice Interface for Elderly-Care

no code implementations20 Jan 2021 Minsu Jang, Sangwon Seo, Dohyung Kim, Jaeyeon Lee, Jaehong Kim, Jun-Hwan Ahn

This paper introduces a large-scale Korean speech dataset, called VOTE400, that can be used for analyzing and recognizing voices of the elderly people.

speech-recognition Speech Recognition

Speech Gesture Generation from the Trimodal Context of Text, Audio, and Speaker Identity

2 code implementations4 Sep 2020 Youngwoo Yoon, Bok Cha, Joo-Haeng Lee, Minsu Jang, Jaeyeon Lee, Jaehong Kim, Geehyuk Lee

In this paper, we present an automatic gesture generation model that uses the multimodal context of speech text, audio, and speaker identity to reliably generate gestures.

Gesture Generation

AIR-Act2Act: Human-human interaction dataset for teaching non-verbal social behaviors to robots

1 code implementation4 Sep 2020 Woo-Ri Ko, Minsu Jang, Jaeyeon Lee, Jaehong Kim

In addition, we provide the joint angles of a humanoid NAO robot which are converted from the human behavior that robots need to learn.

Robotics

ETRI-Activity3D: A Large-Scale RGB-D Dataset for Robots to Recognize Daily Activities of the Elderly

1 code implementation4 Mar 2020 Jinhyeok Jang, Dohyung Kim, Cheonshu Park, Minsu Jang, Jaeyeon Lee, Jaehong Kim

To cope with this situation, we introduce a new dataset called ETRI-Activity3D, focusing on the daily activities of the elderly in robot-view.

Cut-and-Paste Dataset Generation for Balancing Domain Gaps in Object Instance Detection

no code implementations26 Sep 2019 Woo-han Yun, Taewoo Kim, Jaeyeon Lee, Jaehong Kim, Junmo Kim

Then, we show that the original cut-and-paste approach suffers from a new domain gap problem, an unbalanced domain gaps, because it has two separate source domains for foreground and background, unlike the conventional domain shift problem.

Domain Adaptation Generative Adversarial Network +2

Neural Networks with Activation Networks

no code implementations21 Nov 2018 Jinhyeok Jang, Jaehong Kim, Jaeyeon Lee, Seungjoon Yang

This work presents an adaptive activation method for neural networks that exploits the interdependency of features.

Deep Asymmetric Networks with a Set of Node-wise Variant Activation Functions

no code implementations11 Sep 2018 Jinhyeok Jang, Hyunjoong Cho, Jaehong Kim, Jaeyeon Lee, Seungjoon Yang

As a result, features learned by the nodes are sorted by the node indices in the order of their importance.

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