Abstract: Separating the target speech in multi-talker noisy environment is a challenging problem for audio-only source separation algorithms.

In this work, we propose a visual-pilot deep fusion approach to effectively separate the unseen 'visible' target speech from multi-talker noisy environment.

PDF | On May 1, 2020, Yun Li and others published A Visual-Pilot Deep Fusion for Target Speech Separation in Multitalker Noisy Environment | Find, ...

May 5, 2020 · A VISUAL-PILOT DEEP FUSION FOR TARGET SPEECH SEPARATION IN MULTI-TALKER NOISY ENVIRONMENT. Authors, Yun Li, Zhang Liu, Yueyue Na, Ziteng Wang ...

Jul 4, 2022 · In this paper we propose a multi-modal multi-correlation learn- ing framework targeting at the task of audio-visual speech sep- aration.

Apr 16, 2020 · 1: A VISUAL-PILOT DEEP FUSION FOR TARGET SPEECH SEPARATION IN MULTI-TALKER NOISY ENVIRONMENT · 2: C3DVQA: FULL-REFERENCE VIDEO QUALITY ASSESSMENT ...

A visual-pilot deep fusion for target speech separation in multitalker noisy environment. Y Li, Z Liu, Y Na, Z Wang, B Tian, Q Fu. ICASSP 2020-2020 IEEE ...

This document provides a list of resources on audio-visual speech enhancement and separation based on deep learning.

A Visual-Pilot Deep Fusion for Target Speech Separation in Multitalker Noisy Environment. ICASSP 2020: 4442-4446. [c19]. view. electronic edition via DOI (open ...

Aug 8, 2024 · A Visual-Pilot Deep Fusion for Target Speech Separation in Multitalker Noisy Environment. Conference Paper. Full-text available. May 2020. Yun ...