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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
Neural Acoustic Context Field: Rendering Realistic Room Impulse Response With Neural Fields—0
Bayesian inference and neural estimation of acoustic wave propagation—0
Blind identification of Ambisonic reduced room impulse response—0
Estimation of Source and Receiver Positions, Room Geometry and Reflection Coefficients From a Single Room Impulse Response—0
Blind estimation of room acoustic parameters from speech signals based on extended model of room impulse response—0
Relative Acoustic Features for Distance Estimation in Smart-Homes—0
Blind Signal Dereverberation for Machine Speech Recognition—0
Few-Shot Audio-Visual Learning of Environment Acoustics—0
Speech Data Augmentation for Improving Phoneme Transcriptions of Aphasic Speech Using Wav2Vec 2.0 for the PSST Challenge—0
Computing Optimal Location of Microphone for Improved Speech Recognition—0
Impact of Microphone position Measurement Error on Multi Channel Distant Speech Recognition & Intelligibility—0
Geometry-Aware Multi-Task Learning for Binaural Audio Generation from Video—0
A Universal Deep Room Acoustics Estimator—0
Mean absorption estimation from room impulse responses using virtually supervised learning—0
Evaluation of Deep-Learning-Based Voice Activity Detectors and Room Impulse Response Models in Reverberant Environments—0
DASEE A Synthetic Database of Domestic Acoustic Scenes and Events in Dementia Patients Environment—0
TeCANet: Temporal-Contextual Attention Network for Environment-Aware Speech Dereverberation—0
Towards Robust Speech-to-Text Adversarial Attack—0
Small-Footprint Wake Up Word Recognition in Noisy Environments Employing Competing-Words-Based Feature—0
Joint Blind Room Acoustic Characterization From Speech And Music Signals Using Convolutional Recurrent Neural Networks—0
Dereverberation using joint estimation of dry speech signal and acoustic system—0
Real-time, Universal, and Robust Adversarial Attacks Against Speaker Recognition Systems—0
An Image Source Method Framework for Arbitrary Reflecting Boundaries—0
Building and Evaluation of a Real Room Impulse Response Dataset—0
Room Geometry Estimation from Room Impulse Responses using Convolutional Neural Networks—0
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