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Model-Informed Speech Enhancement Using Virtual Room Acoustics and Acoustic Descriptor Optimization
Samuel Yaw Mensah1, Tao Zhang2, Xin Zhao2
1School of Electrical & Information Engineering, Tianjin University, 92 Weijin Road, Nankai District, Tianjin 300072, China.
Sensors (Basel, Switzerland)
|June 26, 2026
Summary
This study introduces a physics-informed algorithm for speech enhancement, reducing reverberation and noise in enclosed spaces. The method improves speech clarity and intelligibility using room acoustics modeling for better performance in diverse environments.
Area of Science:
- Acoustics
- Signal Processing
- Computational Physics
Background:
- Reverberation and noise hinder speech intelligibility in enclosed spaces.
- Conventional dereverberation methods lack robustness and physical interpretability in new acoustic environments.
Purpose of the Study:
- To develop a physics-informed speech enhancement algorithm integrating room acoustics modeling and descriptor-guided optimization.
- To address limitations of conventional methods by improving robustness and interpretability.
Main Methods:
- Employs virtual field simulations based on the Helmholtz equation to estimate acoustic descriptors (RT60, DRR, C50).
- Utilizes estimated descriptors to adaptively control a model-informed dereverberation filter.
- Integrates physical modeling with signal processing for dereverberation.
Main Results:
- Achieved average gains of +6.4 dB in SNR, +1.2 in PESQ, and +0.13 in STOI.
- Demonstrated measurable improvements in reducing reverberation time (RT60) and enhancing clarity (C50).
- Showcased superior performance over baseline methods in simulated and real-room conditions.
Conclusions:
- The proposed hybrid approach offers computational efficiency and interpretability.
- Suitable for real-time deployment in applications like teleconferencing, hearing assistance, and smart audio.
- Effectively minimizes late reverberation while preserving spectral fidelity.
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