# Blind Room Impulse Response Identification via Reverberant Speech Spectrum Reconstruction

arXiv: https://arxiv.org/abs/2509.15628 · HTML: https://mlsanity.com/paper/2509.15628/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Sep 2025.

## Built on by (most cited first, 1 of 1)

- [EchoMark: Perceptual Acoustic Environment Transfer with Watermark-Embedded Room Impulse Response](https://mlsanity.com/paper/2511.06458/) (2025)

## Abstract (arXiv)

This paper proposes Rec-RIR for blind room impulse response (RIR) identification. Based on the convolutive transfer function (CTF) approximation, we propose a multi-task deep neural network, which sequentially removes noise and reverberation from speech recording, and estimates the CTF filter by reverberant speech spectrum reconstruction. Subsequently, a pseudo intrusive measurement process is employed to convert the CTF filter into RIR by simulating a common intrusive RIR measurement procedure. Experimental results demonstrate that Rec-RIR achieves state-of-the-art (SOTA) performance in blind RIR identification.