77 citations · 243 across the 31 of their papers we have counts for
Showing 2017 · stat.MLShow all
3 papers · 2 filters
stat.ML2017★ 20 cited
End-to-End Waveform Utterance Enhancement for Direct Evaluation Metrics Optimization by Fully Convolutional Neural Networks
Szu-Wei Fu, Tao-Wei Wang, Yu Tsao +2
Speech enhancement model is used to map a noisy speech to a clean speech. In the training stage, an objective function is often adopted to optimize the model parameters. However, i…
stat.ML2017★ 12 cited
Complex spectrogram enhancement by convolutional neural network with multi-metrics learning
Szu-Wei Fu, Ting-yao Hu, Yu Tsao +1
This paper aims to address two issues existing in the current speech enhancement methods: 1) the difficulty of phase estimations; 2) a single objective function cannot consider mul…
stat.ML2017★ 35 cited
Raw Waveform-based Speech Enhancement by Fully Convolutional Networks
Szu-Wei Fu, Yu Tsao, Xugang Lu +1
This study proposes a fully convolutional network (FCN) model for raw waveform-based speech enhancement. The proposed system performs speech enhancement in an end-to-end (i.e., wav…