RIR-Former: Coordinate-Guided Transformer for Continuous Reconstruction of Room Impulse Responses
This work addresses the impracticality of dense RIR measurements for acoustic signal processing tasks, offering a practical solution for interpolation in simulated acoustic environments, though it is incremental in its application of transformer architectures to this domain.
The paper tackles the problem of densely measuring room impulse responses (RIRs) by proposing RIR-Former, a transformer-based model that reconstructs RIRs at arbitrary locations, achieving improved performance over state-of-the-art baselines in terms of normalized mean square error and cosine distance across various simulated environments.
Room impulse responses (RIRs) are essential for many acoustic signal processing tasks, yet measuring them densely across space is often impractical. In this work, we propose RIR-Former, a grid-free, one-step feed-forward model for RIR reconstruction. By introducing a sinusoidal encoding module into a transformer backbone, our method effectively incorporates microphone position information, enabling interpolation at arbitrary array locations. Furthermore, a segmented multi-branch decoder is designed to separately handle early reflections and late reverberation, improving reconstruction across the entire RIR. Experiments on diverse simulated acoustic environments demonstrate that RIR-Former consistently outperforms state-of-the-art baselines in terms of normalized mean square error (NMSE) and cosine distance (CD), under varying missing rates and array configurations. These results highlight the potential of our approach for practical deployment and motivate future work on scaling from randomly spaced linear arrays to complex array geometries, dynamic acoustic scenes, and real-world environments.