262 citations · 1.4k across the 109 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…
Voice Conversion from Non-parallel Corpora Using Variational Auto-encoder
Chin-Cheng Hsu, Hsin-Te Hwang, Yi-Chiao Wu +2
We propose a flexible framework for spectral conversion (SC) that facilitates training with unaligned corpora. Many SC frameworks require parallel corpora, phonetic alignments, or…
Dictionary Update for NMF-based Voice Conversion Using an Encoder-Decoder Network
Chin-Cheng Hsu, Hsin-Te Hwang, Yi-Chiao Wu +2
In this paper, we propose a dictionary update method for Nonnegative Matrix Factorization (NMF) with high dimensional data in a spectral conversion (SC) task. Voice conversion has…