25 citations · 32 across the 5 of their papers we have counts for
5 papers
A Unified Compression Framework for Efficient Speech-Driven Talking-Face Generation
Bo-Kyeong Kim, Jaemin Kang, Daeun Seo +5
Virtual humans have gained considerable attention in numerous industries, e.g., entertainment and e-commerce. As a core technology, synthesizing photorealistic face frames from tar…
Cut Inner Layers: A Structured Pruning Strategy for Efficient U-Net GANs
Bo-Kyeong Kim, Shinkook Choi, Hancheol Park
Pruning effectively compresses overparameterized models. Despite the success of pruning methods for discriminative models, applying them for generative models has been relatively r…
Semi-supervised Disentanglement with Independent Vector Variational Autoencoders
Bo-Kyeong Kim, Sungjin Park, Geonmin Kim +1
We aim to separate the generative factors of data into two latent vectors in a variational autoencoder. One vector captures class factors relevant to target classification tasks, w…
Unpaired Speech Enhancement by Acoustic and Adversarial Supervision for Speech Recognition
Geonmin Kim, Hwaran Lee, Bo-Kyeong Kim +2
Many speech enhancement methods try to learn the relationship between noisy and clean speech, obtained using an acoustic room simulator. We point out several limitations of enhance…
Compositional Sentence Representation from Character within Large Context Text
Geonmin Kim, Hwaran Lee, Jisu Choi +1
This paper describes a Hierarchical Composition Recurrent Network (HCRN) consisting of a 3-level hierarchy of compositional models: character, word and sentence. This model is desi…