Room Impulse Response (RIR)

11 papers with code • 0 benchmarks • 0 datasets

Room Impulse Response (RIR) is an audio signal processing task that involves capturing and analyzing the acoustic characteristics of a room or an environment. The goal is to measure and model the way sound waves interact with the space, including reflections, reverberation, and echoes.

Most implemented papers

gpuRIR: A python library for Room Impulse Response simulation with GPU acceleration

DavidDiazGuerra/gpuRIR 26 Oct 2018

The Image Source Method (ISM) is one of the most employed techniques to calculate acoustic Room Impulse Responses (RIRs), however, its computational complexity grows fast with the reverberation time of the room and its computation time can be prohibitive for some applications where a huge number of RIRs are needed.

dEchorate: a Calibrated Room Impulse Response Database for Echo-aware Signal Processing

Chutlhu/dEchorate 27 Apr 2021

This paper presents dEchorate: a new database of measured multichannel Room Impulse Responses (RIRs) including annotations of early echo timings and 3D positions of microphones, real sources and image sources under different wall configurations in a cuboid room.

MeshRIR: A Dataset of Room Impulse Responses on Meshed Grid Points For Evaluating Sound Field Analysis and Synthesis Methods

sh01k/MeshRIR 21 Jun 2021

Two subdatasets are currently available: one consists of IRs in a three-dimensional cuboidal region from a single source, and the other consists of IRs in a two-dimensional square region from an array of 32 sources.

FAST-RIR: Fast neural diffuse room impulse response generator

anton-jeran/FAST-RIR 7 Oct 2021

We present a neural-network-based fast diffuse room impulse response generator (FAST-RIR) for generating room impulse responses (RIRs) for a given acoustic environment.

FRA-RIR: Fast Random Approximation of the Image-source Method

yluo42/fra-rir 8 Aug 2022

The training of modern speech processing systems often requires a large amount of simulated room impulse response (RIR) data in order to allow the systems to generalize well in real-world, reverberant environments.

StoRIR: Stochastic Room Impulse Response Generation for Audio Data Augmentation

SRPOL-AUI/storir 17 Aug 2020

In this paper we introduce StoRIR - a stochastic room impulse response generation method dedicated to audio data augmentation in machine learning applications.

Attack on practical speaker verification system using universal adversarial perturbations

zhang-wy15/Attack_practical_asv 19 May 2021

In authentication scenarios, applications of practical speaker verification systems usually require a person to read a dynamic authentication text.

SofaMyRoom: a fast and multiplatform "shoebox" room simulator for binaural room impulse response dataset generation

spatialaudiotools/sofamyroom 24 Jun 2021

This paper introduces a shoebox room simulator able to systematically generate synthetic datasets of binaural room impulse responses (BRIRs) given an arbitrary set of head-related transfer functions (HRTFs).

Sound Event Localization and Detection for Real Spatial Sound Scenes: Event-Independent Network and Data Augmentation Chains

jinbo-hu/dcase2022-task3 5 Sep 2022

Our system submitted to the DCASE 2022 Task 3 is based on our previous proposed Event-Independent Network V2 (EINV2) with a novel data augmentation method.

BERP: A Blind Estimator of Room Acoustic and Physical Parameters for Single-Channel Noisy Speech Signals

Alizeded/BERP 7 May 2024

On the other hand, in this paper, we propose a novel universal blind estimation framework called the blind estimator of room acoustical and physical parameters (BERP), by introducing a new stochastic room impulse response (RIR) model, namely, the sparse stochastic impulse response (SSIR) model, and endowing the BERP with a unified encoder and multiple separate predictors to estimate RPPs and SSIR parameters in parallel.