51 citations · 100 across the 15 of their papers we have counts for
15 papers
NICE: CVPR 2023 Challenge on Zero-shot Image Captioning
Taehoon Kim, Pyunghwan Ahn, Sangyun Kim +39
In this report, we introduce NICE (New frontiers for zero-shot Image Captioning Evaluation) project and share the results and outcomes of 2023 challenge. This project is designed t…
Open-Vocabulary Object Detection using Pseudo Caption Labels
Han-Cheol Cho, Won Young Jhoo, Wooyoung Kang +1
Recent open-vocabulary detection methods aim to detect novel objects by distilling knowledge from vision-language models (VLMs) trained on a vast amount of image-text pairs. To imp…
Noise-aware Learning from Web-crawled Image-Text Data for Image Captioning
Wooyoung Kang, Jonghwan Mun, Sungjun Lee +1
Image captioning is one of the straightforward tasks that can take advantage of large-scale web-crawled data which provides rich knowledge about the visual world for a captioning m…
Attentive activation function for improving end-to-end spoofing countermeasure systems
Woo Hyun Kang, Jahangir Alam, Abderrahim Fathan
The main objective of the spoofing countermeasure system is to detect the artifacts within the input speech caused by the speech synthesis or voice conversion process. In order to…
Robust Speech Representation Learning via Flow-based Embedding Regularization
Woo Hyun Kang, Jahangir Alam, Abderrahim Fathan
Over the recent years, various deep learning-based methods were proposed for extracting a fixed-dimensional embedding vector from speech signals. Although the deep learning-based e…
Continuous Monitoring of Blood Pressure with Evidential Regression
Hyeongju Kim, Woo Hyun Kang, Hyeonseung Lee +1
Photoplethysmogram (PPG) signal-based blood pressure (BP) estimation is a promising candidate for modern BP measurements, as PPG signals can be easily obtained from wearable device…
Unsupervised Representation Learning for Speaker Recognition via Contrastive Equilibrium Learning
Sung Hwan Mun, Woo Hyun Kang, Min Hyun Han +1
In this paper, we propose a simple but powerful unsupervised learning method for speaker recognition, namely Contrastive Equilibrium Learning (CEL), which increases the uncertainty…
Robust Text-Dependent Speaker Verification via Character-Level Information Preservation for the SdSV Challenge 2020
Sung Hwan Mun, Woo Hyun Kang, Min Hyun Han +1
This paper describes our submission to Task 1 of the Short-duration Speaker Verification (SdSV) challenge 2020. Task 1 is a text-dependent speaker verification task, where both the…
Disentangled speaker and nuisance attribute embedding for robust speaker verification
Woo Hyun Kang, Sung Hwan Mun, Min Hyun Han +1
Over the recent years, various deep learning-based embedding methods have been proposed and have shown impressive performance in speaker verification. However, as in most of the cl…
WaveNODE: A Continuous Normalizing Flow for Speech Synthesis
Hyeongju Kim, Hyeonseung Lee, Woo Hyun Kang +3
In recent years, various flow-based generative models have been proposed to generate high-fidelity waveforms in real-time. However, these models require either a well-trained teach…
Gated Recurrent Context: Softmax-free Attention for Online Encoder-Decoder Speech Recognition
Hyeonseung Lee, Woo Hyun Kang, Sung Jun Cheon +2
Recently, attention-based encoder-decoder (AED) models have shown state-of-the-art performance in automatic speech recognition (ASR). As the original AED models with global attenti…
SoftFlow: Probabilistic Framework for Normalizing Flow on Manifolds
Hyeongju Kim, Hyeonseung Lee, Woo Hyun Kang +2
Flow-based generative models are composed of invertible transformations between two random variables of the same dimension. Therefore, flow-based models cannot be adequately traine…
Text Matters but Speech Influences: A Computational Analysis of Syntactic Ambiguity Resolution
Won Ik Cho, Jeonghwa Cho, Woo Hyun Kang +1
Analyzing how human beings resolve syntactic ambiguity has long been an issue of interest in the field of linguistics. It is, at the same time, one of the most challenging issues f…
Giving Space to Your Message: Assistive Word Segmentation for the Electronic Typing of Digital Minorities
Won Ik Cho, Sung Jun Cheon, Woo Hyun Kang +2
For readability and disambiguation of the written text, appropriate word segmentation is recommended for documentation, and it also holds for the digitized texts. If the language i…
Extracting Arguments from Korean Question and Command: An Annotated Corpus for Structured Paraphrasing
Won Ik Cho, Young Ki Moon, Woo Hyun Kang +1
Intention identification is a core issue in dialog management. However, due to the non-canonicality of the spoken language, it is difficult to extract the content automatically fro…