34 citations · 67 across the 15 of their papers we have counts for
16 papers
USAD 2.0: Scaling Representation Distillation for Universal Audio Understanding
Heng-Jui Chang, Alexander H. Liu, Saurabhchand Bhati +4
Audio encoders are critical to modern audio applications as large language models (LLMs) increasingly rely on a single encoder for diverse inputs. While self-supervised learning (S…
ProSE: Diffusion Priors for Speech Enhancement
Sonal Kumar, Sreyan Ghosh, Utkarsh Tyagi +4
Speech enhancement (SE) is the foundational task of enhancing the clarity and quality of speech in the presence of non-stationary additive noise. While deterministic deep learning…
Efficient learning-based sound propagation for virtual and real-world audio processing applications
Anton Jeran Ratnarajah
Sound propagation is the process by which sound energy travels through a medium, such as air, to the surrounding environment as sound waves. The room impulse response (RIR) describ…
Forensic Video Analytic Software
Anton Jeran Ratnarajah, Sahani Goonetilleke, Dumindu Tissera +2
Law enforcement officials heavily depend on Forensic Video Analytic (FVA) Software in their evidence extraction process. However present-day FVA software are complex, time consumin…
Moving Object Based Collision-Free Video Synopsis
Anton Jeran Ratnarajah, Sahani Goonetilleke, Dumindu Tissera +2
Video synopsis, summarizing a video to generate a shorter video by exploiting the spatial and temporal redundancies, is important for surveillance and archiving. Existing trajector…
AV-RIR: Audio-Visual Room Impulse Response Estimation
Anton Ratnarajah, Sreyan Ghosh, Sonal Kumar +2
Accurate estimation of Room Impulse Response (RIR), which captures an environment's acoustic properties, is important for speech processing and AR/VR applications. We propose AV-RI…
BANC: Towards Efficient Binaural Audio Neural Codec for Overlapping Speech
Anton Ratnarajah, Shi-Xiong Zhang, Dong Yu
We introduce BANC, a neural binaural audio codec designed for efficient speech compression in single and two-speaker scenarios while preserving the spatial location information of…
AdVerb: Visually Guided Audio Dereverberation
Sanjoy Chowdhury, Sreyan Ghosh, Subhrajyoti Dasgupta +3
We present AdVerb, a novel audio-visual dereverberation framework that uses visual cues in addition to the reverberant sound to estimate clean audio. Although audio-only dereverber…
Listen2Scene: Interactive material-aware binaural sound propagation for reconstructed 3D scenes
Anton Ratnarajah, Dinesh Manocha
We present an end-to-end binaural audio rendering approach (Listen2Scene) for virtual reality (VR) and augmented reality (AR) applications. We propose a novel neural-network-based…
Towards Improved Room Impulse Response Estimation for Speech Recognition
Anton Ratnarajah, Ishwarya Ananthabhotla, Vamsi Krishna Ithapu +3
We propose a novel approach for blind room impulse response (RIR) estimation systems in the context of a downstream application scenario, far-field automatic speech recognition (AS…
MESH2IR: Neural Acoustic Impulse Response Generator for Complex 3D Scenes
Anton Ratnarajah, Zhenyu Tang, Rohith Chandrashekar Aralikatti +1
We propose a mesh-based neural network (MESH2IR) to generate acoustic impulse responses (IRs) for indoor 3D scenes represented using a mesh. The IRs are used to create a high-quali…
GWA: A Large High-Quality Acoustic Dataset for Audio Processing
Zhenyu Tang, Rohith Aralikatti, Anton Ratnarajah +1
We present the Geometric-Wave Acoustic (GWA) dataset, a large-scale audio dataset of about 2 million synthetic room impulse responses (IRs) and their corresponding detailed geometr…
FAST-RIR: Fast neural diffuse room impulse response generator
Anton Ratnarajah, Shi-Xiong Zhang, Meng Yu +3
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. Our FAST-RI…
Improving Reverberant Speech Separation with Multi-stage Training and Curriculum Learning
Rohith Aralikatti, Anton Ratnarajah, Zhenyu Tang +1
We present a novel approach that improves the performance of reverberant speech separation. Our approach is based on an accurate geometric acoustic simulator (GAS) which generates…
TS-RIR: Translated synthetic room impulse responses for speech augmentation
Anton Ratnarajah, Zhenyu Tang, Dinesh Manocha
We present a method for improving the quality of synthetic room impulse responses for far-field speech recognition. We bridge the gap between the fidelity of synthetic room impulse…
IR-GAN: Room Impulse Response Generator for Far-field Speech Recognition
Anton Ratnarajah, Zhenyu Tang, Dinesh Manocha
We present a Generative Adversarial Network (GAN) based room impulse response generator (IR-GAN) for generating realistic synthetic room impulse responses (RIRs). IR-GAN extracts a…