514 citations · 1.2k across the 41 of their papers we have counts for
6 papers · 1 filter
STOI-Net: A Deep Learning based Non-Intrusive Speech Intelligibility Assessment Model
Ryandhimas E. Zezario, Szu-Wei Fu, Chiou-Shann Fuh +2
The calculation of most objective speech intelligibility assessment metrics requires clean speech as a reference. Such a requirement may limit the applicability of these metrics in…
Improving Perceptual Quality by Phone-Fortified Perceptual Loss using Wasserstein Distance for Speech Enhancement
Tsun-An Hsieh, Cheng Yu, Szu-Wei Fu +2
Speech enhancement (SE) aims to improve speech quality and intelligibility, which are both related to a smooth transition in speech segments that may carry linguistic information,…
CITISEN: A Deep Learning-Based Speech Signal-Processing Mobile Application
Yu-Wen Chen, Kuo-Hsuan Hung, You-Jin Li +6
This study presents a deep learning-based speech signal-processing mobile application known as CITISEN. The CITISEN provides three functions: speech enhancement (SE), model adaptat…
Waveform-based Voice Activity Detection Exploiting Fully Convolutional networks with Multi-Branched Encoders
Cheng Yu, Kuo-Hsuan Hung, I-Fan Lin +3
In this study, we propose an encoder-decoder structured system with fully convolutional networks to implement voice activity detection (VAD) directly on the time-domain waveform. T…
Boosting Objective Scores of a Speech Enhancement Model by MetricGAN Post-processing
Szu-Wei Fu, Chien-Feng Liao, Tsun-An Hsieh +9
The Transformer architecture has demonstrated a superior ability compared to recurrent neural networks in many different natural language processing applications. Therefore, our st…
iMetricGAN: Intelligibility Enhancement for Speech-in-Noise using Generative Adversarial Network-based Metric Learning
Haoyu Li, Szu-Wei Fu, Yu Tsao +1
The intelligibility of natural speech is seriously degraded when exposed to adverse noisy environments. In this work, we propose a deep learning-based speech modification method to…