Pharmacological Assessment of Aqueous Ethanolic Extract of Against Haloperidol-Induced Parkinson’s Like Symptoms in Animal Model: A Dose-Dependent Study With Mechanistic Approach

Autor: Jiangyu Han, Xu Hao, Mishal Fatima, Zunera Chauhdary, Ayesha Jamshed, Hafiz Muhammad Abdur Rahman, Rida Siddique, Muhammad Asif, Saba Rana, Liaqat Hussain

Publikováno v: Dose-Response, Vol 22 (2024)

Introduction: Parkinson’s disease (PD) is characterized by dopamine deficiency in the corpus striatum due to the degeneration of dopaminergic neurons in the substantia nigra. Symptoms include bradykinesia, resting tremors, unstable posture, muscula

Externí odkaz: https://doaj.org/article/c746d6bcaeb6438f992b5d6515e74288

Heterogeneous separation consistency training for adaptation of unsupervised speech separation

Autor: Jiangyu Han, Yanhua Long

Publikováno v: EURASIP Journal on Audio, Speech, and Music Processing, Vol 2023, Iss 1, Pp 1-17 (2023)

Abstract Recently, supervised speech separation has made great progress. However, limited by the nature of supervised training, most existing separation methods require ground-truth sources and are trained on synthetic datasets. This ground-truth rel

Externí odkaz: https://doaj.org/article/8ec6c0c95713493489578d2f43b2a827

PercepNet+: A Phase and SNR Aware PercepNet for Real-Time Speech Enhancement

Autor: Xiaofeng Ge, Jiangyu Han, Yanhua Long, Haixin Guan

PercepNet, a recent extension of the RNNoise, an efficient, high-quality and real-time full-band speech enhancement technique, has shown promising performance in various public deep noise suppression tasks. This paper proposes a new approach, named P

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d3bb0a55e74d17d194b04741f845e4c2
http://arxiv.org/abs/2203.02263

DPCCN: Densely-Connected Pyramid Complex Convolutional Network for Robust Speech Separation And Extraction

Autor: Jiangyu Han, Yanhua Long, Lukas Burget, Jan Cernocky

In recent years, a number of time-domain speech separation methods have been proposed. However, most of them are very sensitive to the environments and wide domain coverage tasks. In this paper, from the time-frequency domain perspective, we propose

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::790340ef962e02f7c8524d23fe003cf6
http://arxiv.org/abs/2112.13520

ConferencingSpeech Challenge:Towards Far-field Multi-Channel Speech Enhancement for Video Conferencing

Autor: Wei Rao, Yihui Fu, Yanxin Hu, Xin Xu, Yvkai Jv, Jiangyu Han, Zhongjie Jiang, Lei Xie, Yannan Wang, Shinji Watanabe, Zheng-Hua Tan, Hui Bu, Tao Yu, Shidong Shang

Publikováno v: Rao, W, Fu, Y, Hu, Y, Xu, X, Jv, Y, Han, J, Jiang, Z, Xie, L, Wang, Y, Watanabe, S, Tan, Z-H, Bu, H, Yu, T & Shang, S 2021, ConferencingSpeech Challenge : Towards Far-field Multi-Channel Speech Enhancement for Video Conferencing . in IEEE Automatic Speech Recognition and Understanding Workshop ., 9688126, IEEE, IEEE Automatic Speech Recognition and Understanding Workshop, 13/12/2021 . https://doi.org/10.1109/ASRU51503.2021.9688126

The ConferencingSpeech 2021 challenge is proposed to stimulate research on far-field multi-channel speech enhancement for video conferencing. The challenge consists of two separate tasks: 1) Task 1 is multi-channel speech enhancement with single micr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2d3ccb80030522588703804dab2c229
https://vbn.aau.dk/da/publications/e3d2e75c-f42b-4149-9b1a-20e9b61fe583