Zobrazeno 1 - 10
of 1 247
pro vyhledávání: '"speech restoration"'
In this paper, we introduce a novel general speech restoration model: the Dual-path Magnitude (DM) network, designed to address multiple distortions including noise, reverberation, and bandwidth degradation effectively. The DM network employs dual pa
Externí odkaz:
http://arxiv.org/abs/2409.08702
Noise suppression (NS) algorithms are effective in improving speech quality in many cases. However, aggressive noise suppression can damage the target speech, reducing both speech intelligibility and quality despite removing the noise. This study pro
Externí odkaz:
http://arxiv.org/abs/2409.06126
Traditional speech enhancement methods often oversimplify the task of restoration by focusing on a single type of distortion. Generative models that handle multiple distortions frequently struggle with phone reconstruction and high-frequency harmonic
Externí odkaz:
http://arxiv.org/abs/2409.11145
Speech restoration aims at restoring full-band speech with high quality and intelligibility, considering a diverse set of distortions. MaskSR is a recently proposed generative model for this task. As other models of its kind, MaskSR attains high qual
Externí odkaz:
http://arxiv.org/abs/2409.09357
Speech restoration aims at restoring high quality speech in the presence of a diverse set of distortions. Although several deep learning paradigms have been studied for this task, the power of the recently emerging language models has not been fully
Externí odkaz:
http://arxiv.org/abs/2406.02092
Autor:
Yu, Guochen, Han, Runqiang, Xu, Chenglin, Zhao, Haoran, Li, Nan, Zhang, Chen, Zheng, Xiguang, Zhou, Chao, Huang, Qi, Yu, Bing
This paper presents the speech restoration and enhancement system created by the 1024K team for the ICASSP 2024 Speech Signal Improvement (SSI) Challenge. Our system consists of a generative adversarial network (GAN) in complex-domain for speech rest
Externí odkaz:
http://arxiv.org/abs/2402.01808
This paper introduces an end-to-end neural speech restoration model, HD-DEMUCS, demonstrating efficacy across multiple distortion environments. Unlike conventional approaches that employ cascading frameworks to remove undesirable noise first and then
Externí odkaz:
http://arxiv.org/abs/2306.01411
Enhancing speech quality is an indispensable yet difficult task as it is often complicated by a range of degradation factors. In addition to additive noise, reverberation, clipping, and speech attenuation can all adversely affect speech quality. Spee
Externí odkaz:
http://arxiv.org/abs/2305.18739
Autor:
Koizumi, Yuma, Zen, Heiga, Karita, Shigeki, Ding, Yifan, Yatabe, Kohei, Morioka, Nobuyuki, Zhang, Yu, Han, Wei, Bapna, Ankur, Bacchiani, Michiel
Speech restoration (SR) is a task of converting degraded speech signals into high-quality ones. In this study, we propose a robust SR model called Miipher, and apply Miipher to a new SR application: increasing the amount of high-quality training data
Externí odkaz:
http://arxiv.org/abs/2303.01664
Publikováno v:
ICASSP 2023 - IEEE International Conference on Acoustics, Speech and Signal Processing
Diffusion-based generative models have had a high impact on the computer vision and speech processing communities these past years. Besides data generation tasks, they have also been employed for data restoration tasks like speech enhancement and der
Externí odkaz:
http://arxiv.org/abs/2211.02397