1. Home
2. Premium
3. IEEE ICASSP 2020 Virtual Conference May 2020
4. Enhancing End-To-End Multi-Channel Speech Separation Via Spatial Feature Learning

Enhancing End-To-End Multi-Channel Speech Separation Via Spatial Feature Learning

Collection:

IEEE ICASSP 2020 Virtual Conference May 2020

Hand-crafted spatial features (e.g., inter-channel phase difference, IPD) play a fundamental role in recent deep learning based multi-channel speech separation (MCSS) methods. However, these manually designed spatial features are hard to incorporate into

• IEEE MemberUS $11.00
• Society MemberUS $0.00
• IEEE Student MemberUS $11.00
• Non-IEEE MemberUS $15.00

Purchase

Videos in this product

Enhancing End-To-End Multi-Channel Speech Separation Via Spatial Feature Learning

00:13:18

0 views

Hand-crafted spatial features (e.g., inter-channel phase difference, IPD) play a fundamental role in recent deep learning based multi-channel speech separation (MCSS) methods. However, these manually designed spatial features are hard to incorporate into