RIR2FDN: An improved room impulse response analysis and synthesis

Gloria Dal Santo, Benoit Alary, Karolina Prawda, Sebastian J. Schlecht, and Vesa Välimäki

Companion page for the paper submitted to the 27th International Conference on Audio Effcts (DAFx24), Guilford, UK, 3-7 September 2024 .

This page contains the sound examples utilized in the listening test outlined in the paper. The reverberated sounds are categorized by sound source, such as drum loop, speech, and saxophone, as well as by target room impulse response.

This page is still under construction. More material will be uploaded soon.


This paper improves the current state-of-the-art in delay-network-based analysis-synthesis of measured room impulse responses (RIRs). We propose an informed method incorporating improved energy decay estimation and synthesis within an optimized feedback delay network. The performance of the presented method is compared against an end-to-end deep learning approach. A formal listening test was conducted where participants assessed the similarity of reverberated material across seven distinct RIRs and three different sound sources. The results reveal that the performance of these methods is influenced by both the excitation sounds and the reverberation conditions. Nonetheless, the proposed method consistently demonstrates higher similarity ratings compared to the end-to-end approach across most conditions. However, achieving a perfect synthesis of measured RIRs remains a persistent challenge, underscoring the complexity of this problem. Overall, this work helps improve the sound quality of analysis-based artificial reverberation.

RIR EDC information

The RIR used in the evaluation can be downloaded from MIT Survey RIR ID: h229 h025 h042 h110 h027 h163 h001