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Room Impulse Response (RIR)

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.

Papers

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Showing 26–50 of 52 papers

TitleStatusHype
Room Geometry Estimation from Room Impulse Responses using Convolutional Neural Networks—0
Room impulse response prototyping using receiver distance estimations for high quality room equalisation algorithms—0
Small-Footprint Wake Up Word Recognition in Noisy Environments Employing Competing-Words-Based Feature—0
Speech Data Augmentation for Improving Phoneme Transcriptions of Aphasic Speech Using Wav2Vec 2.0 for the PSST Challenge—0
STC Speaker Recognition Systems for the VOiCES From a Distance Challenge—0
An Image Source Method Framework for Arbitrary Reflecting Boundaries—0
Text-Queried Target Sound Event Localization—0
Towards Robust Speech-to-Text Adversarial Attack—0
Unsupervised Blind Joint Dereverberation and Room Acoustics Estimation with Diffusion Models—0
TeCANet: Temporal-Contextual Attention Network for Environment-Aware Speech Dereverberation—0
A Universal Deep Room Acoustics Estimator—0
Bayesian inference and neural estimation of acoustic wave propagation—0
Blind estimation of room acoustic parameters from speech signals based on extended model of room impulse response—0
Blind identification of Ambisonic reduced room impulse response—0
Blind Signal Dereverberation for Machine Speech Recognition—0
Building and Evaluation of a Real Room Impulse Response Dataset—0
Computing Optimal Location of Microphone for Improved Speech Recognition—0
DASEE A Synthetic Database of Domestic Acoustic Scenes and Events in Dementia Patients Environment—0
Data Augmentation Using Neural Acoustic Fields With Retrieval-Augmented Pre-training—0
Dereverberation using joint estimation of dry speech signal and acoustic system—0
Direction-Aware Neural Acoustic Fields for Few-Shot Interpolation of Ambisonic Impulse Responses—0
Estimation of Source and Receiver Positions, Room Geometry and Reflection Coefficients From a Single Room Impulse Response—0
Evaluation of Deep-Learning-Based Voice Activity Detectors and Room Impulse Response Models in Reverberant Environments—0
Few-Shot Audio-Visual Learning of Environment Acoustics—0
Geometry-Aware Multi-Task Learning for Binaural Audio Generation from Video—0
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