7.5k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- NAVER Cloud (South Korea)KR46 papers
- Seoul National UniversityKR27 papers
- Korea Advanced Institute of Science and TechnologyKR24 papers
- Yonsei UniversityKR17 papers
- Sungkyunkwan UniversityKR12 papers
- Korea UniversityKR9 papers
- Line Corporation (Japan)JP5 papers
- Virginia TechUS5 papers
- Inha UniversityKR4 papers
- Kootenay Association for Science & TechnologyCA4 papers
- University of TorontoCA4 papers
- Hong Kong University of Science and TechnologyHK3 papers
31 papers · 1 filter
A Distributional Approach to Controlled Text Generation
Muhammad Khalifa, Hady Elsahar, Marc Dymetman
We propose a Distributional Approach for addressing Controlled Text Generation from pre-trained Language Models (LMs). This approach permits to specify, in a single formal framewor…
Robust Learning by Self-Transition for Handling Noisy Labels
Hwanjun Song, Minseok Kim, Dongmin Park +2
Real-world data inevitably contains noisy labels, which induce the poor generalization of deep neural networks. It is known that the network typically begins to rapidly memorize fa…
Continual Adaptation of Visual Representations via Domain Randomization and Meta-learning
Riccardo Volpi, Diane Larlus, Grégory Rogez
Most standard learning approaches lead to fragile models which are prone to drift when sequentially trained on samples of a different nature - the well-known "catastrophic forgetti…
Distilling a Hierarchical Policy for Planning and Control via Representation and Reinforcement Learning
Jung-Su Ha, Young-Jin Park, Hyeok-Joo Chae +2
We present a hierarchical planning and control framework that enables an agent to perform various tasks and adapt to a new task flexibly. Rather than learning an individual policy…
TTS-by-TTS: TTS-driven Data Augmentation for Fast and High-Quality Speech Synthesis
Min-Jae Hwang, Ryuichi Yamamoto, Eunwoo Song +1
In this paper, we propose a text-to-speech (TTS)-driven data augmentation method for improving the quality of a non-autoregressive (AR) TTS system. Recently proposed non-AR models,…
Information Source Finding in Networks: Querying with Budgets
Jaeyoung Choi, Sangwoo Moon, Jiin Woo +3
In this paper, we study a problem of detecting the source of diffused information by querying individuals, given a sample snapshot of the information diffusion graph, where two que…
Is Retriever Merely an Approximator of Reader?
Sohee Yang, Minjoon Seo
The state of the art in open-domain question answering (QA) relies on an efficient retriever that drastically reduces the search space for the expensive reader. A rather overlooked…
Parallel waveform synthesis based on generative adversarial networks with voicing-aware conditional discriminators
Ryuichi Yamamoto, Eunwoo Song, Min-Jae Hwang +1
This paper proposes voicing-aware conditional discriminators for Parallel WaveGAN-based waveform synthesis systems. In this framework, we adopt a projection-based conditioning meth…
Two-stage Textual Knowledge Distillation for End-to-End Spoken Language Understanding
Seongbin Kim, Gyuwan Kim, Seongjin Shin +1
End-to-end approaches open a new way for more accurate and efficient spoken language understanding (SLU) systems by alleviating the drawbacks of traditional pipeline systems. Previ…
HyperTendril: Visual Analytics for User-Driven Hyperparameter Optimization of Deep Neural Networks
Heungseok Park, Yoonsoo Nam, Ji-Hoon Kim +1
To mitigate the pain of manually tuning hyperparameters of deep neural networks, automated machine learning (AutoML) methods have been developed to search for an optimal set of hyp…
SUMBT+LaRL: Effective Multi-domain End-to-end Neural Task-oriented Dialog System
Hwaran Lee, Seokhwan Jo, HyungJun Kim +2
The recent advent of neural approaches for developing each dialog component in task-oriented dialog systems has remarkably improved, yet optimizing the overall system performance r…
Interactive and Explainable Point-of-Interest Recommendation using Look-alike Groups
Behrooz Omidvar-Tehrani, Sruthi Viswanathan, Jean-Michel Renders
Recommending Points-of-Interest (POIs) is surfacing in many location-based applications. The literature contains personalized and socialized POI recommendation approaches which emp…
Character Region Attention For Text Spotting
Youngmin Baek, Seung Shin, Jeonghun Baek +4
A scene text spotter is composed of text detection and recognition modules. Many studies have been conducted to unify these modules into an end-to-end trainable model to achieve be…
Robust Image Retrieval-based Visual Localization using Kapture
Martin Humenberger, Yohann Cabon, Nicolas Guerin +7
Visual localization tackles the challenge of estimating the camera pose from images by using correspondence analysis between query images and a map. This task is computation and da…
Spot the conversation: speaker diarisation in the wild
Joon Son Chung, Jaesung Huh, Arsha Nagrani +2
The goal of this paper is speaker diarisation of videos collected 'in the wild'. We make three key contributions. First, we propose an automatic audio-visual diarisation method for…
CLEval: Character-Level Evaluation for Text Detection and Recognition Tasks
Youngmin Baek, Daehyun Nam, Sungrae Park +5
Despite the recent success of text detection and recognition methods, existing evaluation metrics fail to provide a fair and reliable comparison among those methods. In addition, t…
Boosting Active Learning for Speech Recognition with Noisy Pseudo-labeled Samples
Jihwan Bang, Heesu Kim, YoungJoon Yoo +1
The cost of annotating transcriptions for large speech corpora becomes a bottleneck to maximally enjoy the potential capacity of deep neural network-based automatic speech recognit…
FrostNet: Towards Quantization-Aware Network Architecture Search
Taehoon Kim, YoungJoon Yoo, Jihoon Yang
INT8 quantization has become one of the standard techniques for deploying convolutional neural networks (CNNs) on edge devices to reduce the memory and computational resource usage…
AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights
Byeongho Heo, Sanghyuk Chun, Seong Joon Oh +5
Normalization techniques are a boon for modern deep learning. They let weights converge more quickly with often better generalization performances. It has been argued that the norm…
FaceFilter: Audio-visual speech separation using still images
Soo-Whan Chung, Soyeon Choe, Joon Son Chung +1
The objective of this paper is to separate a target speaker's speech from a mixture of two speakers using a deep audio-visual speech separation network. Unlike previous works that…
Seeing voices and hearing voices: learning discriminative embeddings using cross-modal self-supervision
Soo-Whan Chung, Hong Goo Kang, Joon Son Chung
The goal of this work is to train discriminative cross-modal embeddings without access to manually annotated data. Recent advances in self-supervised learning have shown that effec…
Few-shot Compositional Font Generation with Dual Memory
Junbum Cha, Sanghyuk Chun, Gayoung Lee +3
Generating a new font library is a very labor-intensive and time-consuming job for glyph-rich scripts. Despite the remarkable success of existing font generation methods, they have…
Spatial Dependency Parsing for Semi-Structured Document Information Extraction
Wonseok Hwang, Jinyeong Yim, Seunghyun Park +2
Information Extraction (IE) for semi-structured document images is often approached as a sequence tagging problem by classifying each recognized input token into one of the IOB (In…
In defence of metric learning for speaker recognition
Joon Son Chung, Jaesung Huh, Seongkyu Mun +7
The objective of this paper is 'open-set' speaker recognition of unseen speakers, where ideal embeddings should be able to condense information into a compact utterance-level repre…