معرفی
Ziye Yang is a researcher active in Speech Signal Processing and Machine Learning applications. His work focuses on advanced techniques like weighted prediction error, deep learning models, and noise reduction in audio systems. He has collaborated extensively with Jie Chen and Cédric Richard on topics including speech dereverberation and nonlinear residual echo suppression.
His research spans multiple subfields including distributed speech processing, attention-based architectures, and deconvolution regularization. Recent publications (2024-2025) emphasize hybrid methods combining traditional signal processing with modern neural networks, particularly for reverberation modeling and echo suppression.
Key trends in his work include
- Integration of data-driven priors in signal enhancement
- Development of plug-and-play frameworks for audio processing
- Application of attention mechanisms in dual-stream networks
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