mlsanityData to 7 Oct 2026

Room Impulse Response Completion Using Signal-Prediction Diffusion Models Conditioned on Simulated Early Reflections

arXiv 2603.12442 ↗First posted 12 Mar 2026eess.AScited by 0

On the map: Diffusion models → Audio, speech and music

Abstract (arXiv)

Room impulse responses (RIRs) are fundamental to audio data augmentation, acoustic signal processing, and immersive audio rendering. While geometric simulators such as the image source method (ISM) can efficiently generate early reflections, they lack the realism of measured RIRs due to missing acoustic wave effects. We propose a diffusion-based RIR completion method using signal-prediction conditioned on ISM-simulated direct-path and early reflections. Unlike state-of-the-art methods, our approach imposes no fixed duration constraint on the input early reflections. We further incorporate classifier-free guidance to steer generation toward a target distribution learned from physically realistic RIRs simulated with the Treble SDK. Objective evaluation demonstrates that the proposed method outperforms a state-of-the-art baseline in early RIR completion and energy decay curve reconstruction.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Audio, speech and music, one of 14 directions in Diffusion models. Builds on 11 of its 24 references that are in the map. First posted on arXiv 12 Mar 2026.

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11 of 24 references.

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Same direction, newest first

  1. 2026Gencho: Room Impulse Response Generation from Reverberant Speech and Text via Diffusion Transformers9 Feb

Other references · 10

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2022Classifier-Free Diffusion Guidancecited by 5,717
  3. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  4. 2017Pyroomacoustics: A Python package for audio room simulations and array processing algorithmscited by 131
  5. 2022Learning Neural Acoustic Fieldscited by 65
  6. 2021FAST-RIR: Fast neural diffuse room impulse response generatorcited by 35
  7. 2024Room impulse response reconstruction with physics-informed deep learningcited by 10
  8. 2024Deep Room Impulse Response Completioncited by 4
  9. 2025Room-acoustic simulations as an alternative to measurements for audio-algorithm evaluationcited by 3
  10. 2023Simulating room transfer functions between transducers mounted on audio devices using a modified image source methodcited by 1

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  1. 2025DiffusionRIR: Room Impulse Response Interpolation using Diffusion Models
  2. 2025Room Impulse Response Generation Conditioned on Acoustic Parameters
  3. 2025PromptReverb: Multimodal Room Impulse Response Generation Through Latent Rectified Flow Matching
  4. 2026EigeNet: Geometry-Informed Multi-Modal Learning for Few-shot Novel View RIR Prediction
  5. 2026Few-shot Acoustic Synthesis with Multimodal Flow Matching
  6. 2026Ambisonics Encoding of Room Impulse Responses using a Device-Agnostic Diffusion Model
  7. 2023Reconstruction of Sound Field through Diffusion Models
  8. 2025DARAS: Dynamic Audio-Room Acoustic Synthesis for Blind Room Impulse Response Estimation ↗