62 citations · 116 across the 14 of their papers we have counts for
4 papers · 1 filter
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…
End-to-end Multimodal Emotion and Gender Recognition with Dynamic Joint Loss Weights
Myungsu Chae, Tae-Ho Kim, Young Hoon Shin +2
Multi-task learning is a method for improving the generalizability of multiple tasks. In order to perform multiple classification tasks with one neural network model, the losses of…
A Fully Time-domain Neural Model for Subband-based Speech Synthesizer
Azam Rabiee, Geonmin Kim, Tae-Ho Kim +1
This paper introduces a deep neural network model for subband-based speech synthesizer. The model benefits from the short bandwidth of the subband signals to reduce the complexity…
Voice Imitating Text-to-Speech Neural Networks
Younggun Lee, Taesu Kim, Soo-Young Lee
We propose a neural text-to-speech (TTS) model that can imitate a new speaker's voice using only a small amount of speech sample. We demonstrate voice imitation using only a 6-seco…