7 citations · 9 across the 6 of their papers we have counts for
6 papers
BASPRO: a balanced script producer for speech corpus collection based on the genetic algorithm
Yu-Wen Chen, Hsin-Min Wang, Yu Tsao
The performance of speech-processing models is heavily influenced by the speech corpus that is used for training and evaluation. In this study, we propose BAlanced Script PROducer…
InQSS: a speech intelligibility and quality assessment model using a multi-task learning network
Yu-Wen Chen, Yu Tsao
Speech intelligibility and quality assessment models are essential tools for researchers to evaluate and improve speech processing models. However, only a few studies have investig…
The AS-NU System for the M2VoC Challenge
Cheng-Hung Hu, Yi-Chiao Wu, Wen-Chin Huang +6
This paper describes the AS-NU systems for two tracks in MultiSpeaker Multi-Style Voice Cloning Challenge (M2VoC). The first track focuses on using a small number of 100 target utt…
EMA2S: An End-to-End Multimodal Articulatory-to-Speech System
Yu-Wen Chen, Kuo-Hsuan Hung, Shang-Yi Chuang +4
Synthesized speech from articulatory movements can have real-world use for patients with vocal cord disorders, situations requiring silent speech, or in high-noise environments. In…
A Study of Incorporating Articulatory Movement Information in Speech Enhancement
Yu-Wen Chen, Kuo-Hsuan Hung, Shang-Yi Chuang +3
Although deep learning algorithms are widely used for improving speech enhancement (SE) performance, the performance remains limited under highly challenging conditions, such as un…
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…