3 citations · 3 across the 3 of their papers we have counts for
3 papers
eess.AS2022
The PCG-AIID System for L3DAS22 Challenge: MIMO and MISO convolutional recurrent Network for Multi Channel Speech Enhancement and Speech Recognition
Jingdong Li, Yuanyuan Zhu, Dawei Luo +3
This paper described the PCG-AIID system for L3DAS22 challenge in Task 1: 3D speech enhancement in office reverberant environment. We proposed a two-stage framework to address mult…
cs.SD2020
Single Channel Speech Enhancement Using Temporal Convolutional Recurrent Neural Networks
Jingdong Li, Hui Zhang, Xueliang Zhang +1
In recent decades, neural network based methods have significantly improved the performace of speech enhancement. Most of them estimate time-frequency (T-F) representation of targe…
cs.CL2019★ 3 cited
Teacher-Student Training for Robust Tacotron-based TTS
Rui Liu, Berrak Sisman, Jingdong Li +3
While neural end-to-end text-to-speech (TTS) is superior to conventional statistical methods in many ways, the exposure bias problem in the autoregressive models remains an issue t…