IEEE SP Cup 2026 | Team SuperZooooom | Two-Stage Speech Enhancement Framework for Audio Zooming скачать в хорошем качестве

IEEE SP Cup 2026 | Team SuperZooooom | Two-Stage Speech Enhancement Framework for Audio Zooming

A Dual-Microphone Two-Stage Speech Enhancement Framework for Audio Zooming  Team SuperZooooom for IEEE Signal Processing CUP 2026 Students: Zhixiang Tang, Yanxin Tian, Gengyou Liu, Yongyi Deng Tutor: Yujie Zhu Supervisor: Gongping Huang  Audio zooming aims to enhance interested sound sources aligned with visual focus while suppressing interference sources, which is particularly challenging for dual-microphone smartphones due to limited spatial resolution and constrained computational resources. Existing methods either suffer from degraded spatial selectivity in adverse acoustic conditions or rely on computationally intensive models that are unsuitable for on-device deployment. This paper proposes a two-stage cascaded audio–visual zooming framework for dual-microphone smartphones, achieving consistent improvements under both anechoic and reverberant conditions. In the first stage, a directionally guided enhancement network exploits directional priors by comparing observed inter-microphone phase differences (IPDs) with theoretical IPDs, thereby improving spatial separation. In the second stage, a single-channel enhancement model is used to jointly refine amplitude and phase spectra and suppress residual noise, where knowledge distillation is applied to reduce model com plexity. Experiments conducted following the IEEE Signal Process ing Cup 2026 protocol show significant improvements in OSINR, SI-SNR, STOI, PESQ and ViSQOL, proving the effectiveness and competitiveness of the proposed framework.  School of Electronic Information Wuhan University