47 citations · 99 across the 7 of their papers we have counts for
7 papers
An Intra-BRNN and GB-RVQ Based END-TO-END Neural Audio Codec
Linping Xu, Jiawei Jiang, Dejun Zhang +7
Recently, neural networks have proven to be effective in performing speech coding task at low bitrates. However, under-utilization of intra-frame correlations and the error of quan…
Harmonic enhancement using learnable comb filter for light-weight full-band speech enhancement model
Xiaohuai Le, Tong Lei, Li Chen +9
With fewer feature dimensions, filter banks are often used in light-weight full-band speech enhancement models. In order to further enhance the coarse speech in the sub-band domain…
Personalized speech enhancement combining band-split RNN and speaker attentive module
Xiaohuai Le, Li Chen, Chao He +4
Target speaker information can be utilized in speech enhancement (SE) models to more effectively extract the desired speech. Previous works introduce the speaker embedding into spe…
Two-stage Neural Network for ICASSP 2023 Speech Signal Improvement Challenge
Mingshuai Liu, Shubo Lv, Zihan Zhang +6
In ICASSP 2023 speech signal improvement challenge, we developed a dual-stage neural model which improves speech signal quality induced by different distortions in a stage-wise div…
A Lottery Ticket Hypothesis Framework for Low-Complexity Device-Robust Neural Acoustic Scene Classification
Hao Yen, Chao-Han Huck Yang, Hu Hu +9
We propose a novel neural model compression strategy combining data augmentation, knowledge transfer, pruning, and quantization for device-robust acoustic scene classification (ASC…
A Two-Stage Approach to Device-Robust Acoustic Scene Classification
Hu Hu, Chao-Han Huck Yang, Xianjun Xia +13
To improve device robustness, a highly desirable key feature of a competitive data-driven acoustic scene classification (ASC) system, a novel two-stage system based on fully convol…
Device-Robust Acoustic Scene Classification Based on Two-Stage Categorization and Data Augmentation
Hu Hu, Chao-Han Huck Yang, Xianjun Xia +13
In this technical report, we present a joint effort of four groups, namely GT, USTC, Tencent, and UKE, to tackle Task 1 - Acoustic Scene Classification (ASC) in the DCASE 2020 Chal…