THE USTC SYSTEM FOR CADENZA 2024 CHALLENGE<bold> </bold>

被引：0

作者：

Lan, Hongbo ^{[1
]}

Cheng, Tianyou ^{[1
]}

He, Maokui ^{[1
]}

Chen, Hang ^{[1
]}

Du, Jun ^{[1
]}

机构：

[1] Univ Sci & Technol China, Hefei, Peoples R China

来源：

2024 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING WORKSHOPS, ICASSPW 2024 | 2024年

基金：

中国国家自然科学基金;

关键词：

Music separation; Hearing aids; Rebalance; Music quality<bold>; </bold>;

D O I：

10.1109/ICASSPW62465.2024.10627147

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

This paper reports our submission to the ICASSP 2024 Cadenza Challenge, focusing on the non-causal system. The challenge aims to develop a signal processing system that enables personalized rebalancing of music to improve the listening experience for individuals with hearing loss when they listen to music via their hearing aids. The system is based on the Hybrid Demucs model. We fine-tuned the baseline model on the given dataset with a multi-target strategy and added a mixture of information in the downmixing stage. We combined different models and achieved a score of 0.6878 in the Hearing Aid Audio Quality Index (HAAQI) metric on the validation set and 0.5929 on the test set.<bold> </bold>

引用

页码：57 / 58

页数：2