262 citations · 1.4k across the 109 of their papers we have counts for
7 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…
Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks
Jen-Cheng Hou, Syu-Siang Wang, Ying-Hui Lai +3
Speech enhancement (SE) aims to reduce noise in speech signals. Most SE techniques focus only on addressing audio information. In this work, inspired by multimodal learning, which…
Adaptive Noise Cancellation Using Deep Cerebellar Model Articulation Controller
Yu Tsao, Hao-Chun Chu, Shih-Wei Lan +3
This paper proposes a deep cerebellar model articulation controller (DCMAC) for adaptive noise cancellation (ANC). We expand upon the conventional CMAC by stacking sin-gle-layer CM…
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…
Voice Conversion from Unaligned Corpora using Variational Autoencoding Wasserstein Generative Adversarial Networks
Chin-Cheng Hsu, Hsin-Te Hwang, Yi-Chiao Wu +2
Building a voice conversion (VC) system from non-parallel speech corpora is challenging but highly valuable in real application scenarios. In most situations, the source and the ta…
Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks
Jen-Cheng Hou, Syu-Siang Wang, Ying-Hui Lai +3
Speech enhancement (SE) aims to reduce noise in speech signals. Most SE techniques focus only on addressing audio information. In this work, inspired by multimodal learning, which…
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…