most citedStable Training of DNN for Speech Enhancement based on Perceptually-Motivated Black-Box Cost Function

1 citations · 1 across the 1 of their papers we have counts for

collaborators

2 papers

eess.AS2021

Noisy-target Training: A Training Strategy for DNN-based Speech Enhancement without Clean Speech

Takuya Fujimura, Yuma Koizumi, Kohei Yatabe +1

Deep neural network (DNN)-based speech enhancement ordinarily requires clean speech signals as the training target. However, collecting clean signals is very costly because they mu…

eess.AS2020★ 1 cited

Stable Training of DNN for Speech Enhancement based on Perceptually-Motivated Black-Box Cost Function

Masaki Kawanaka, Yuma Koizumi, Ryoichi Miyazaki +1

Improving subjective sound quality of enhanced signals is one of the most important missions in speech enhancement. For evaluating the subjective quality, several methods related t…