{"ID":2868626,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.15628","arxiv_id":"2509.15628","title":"Rec-RIR: Monaural Blind Room Impulse Response Identification via DNN-based Reverberant Speech Reconstruction in STFT Domain","abstract":"This paper presents Rec-RIR for monaural blind room impulse response (RIR) identification. Rec-RIR is developed based on the convolutive transfer function (CTF) approximation, which models reverberation effect within narrow-band filter banks in the short-time Fourier transform domain. Specifically, we propose a deep neural network (DNN) with cross-band and narrow-band blocks to estimate the CTF filter. The DNN is trained through reconstructing the noise-free reverberant speech spectra. This objective enables stable and straightforward supervised training. Subsequently, a pseudo intrusive measurement process is employed to convert the CTF filter estimate into RIR by simulating a common intrusive RIR measurement procedure. Experimental results demonstrate that Rec-RIR achieves state-of-the-art performance in both RIR identification and acoustic parameter estimation. Open-source codes are available online at https://github.com/Audio-WestlakeU/Rec-RIR.","short_abstract":"This paper presents Rec-RIR for monaural blind room impulse response (RIR) identification. Rec-RIR is developed based on the convolutive transfer function (CTF) approximation, which models reverberation effect within narrow-band filter banks in the short-time Fourier transform domain. Specifically, we propose a deep ne...","url_abs":"https://arxiv.org/abs/2509.15628","url_pdf":"https://arxiv.org/pdf/2509.15628v2","authors":"[\"Pengyu Wang\",\"Xiaofei Li\"]","published":"2025-09-19T05:45:19Z","proceeding":"eess.AS","tasks":"[\"eess.AS\",\"eess.SP\"]","methods":"[]","has_code":false,"code_links":[{"ID":609607,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2868626,"paper_url":"https://arxiv.org/abs/2509.15628","paper_title":"Rec-RIR: Monaural Blind Room Impulse Response Identification via DNN-based Reverberant Speech Reconstruction in STFT Domain","repo_url":"https://github.com/Audio-WestlakeU/Rec-RIR","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}