Search Results for author:
Found 13 papers, 4 papers with code
Synthetic Wave-Geometric Impulse Responses for Improved Speech Dereverberation
We present a novel approach to improve the performance of learning-based speech dereverberation using accurate synthetic datasets.
MESH2IR: Neural Acoustic Impulse Response Generator for Complex 3D Scenes
We show that the acoustic metrics of the IRs predicted from our MESH2IR match the ground truth with less than 10% error.
FAST-RIR: Fast neural diffuse room impulse response generator
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.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Improving Reverberant Speech Separation with Multi-stage Training and Curriculum Learning
We present a novel approach that improves the performance of reverberant speech separation.
Online Self-Attentive Gated RNNs for Real-Time Speaker Separation
Our stateful implementation for online separation leads to a minor drop in performance compared to the offline model; 0. 8dB for monaural inputs and 0. 3dB for binaural inputs while reaching a real-time factor of 0. 65.
Scene-aware Far-field Automatic Speech Recognition
We use a deep learning-based estimator to non-intrusively compute the sub-band reverberation time of an environment from its speech samples.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Fast 3D Acoustic Scattering via Discrete Laplacian Based Implicit Function Encoders
Acoustic properties of objects corresponding to scattering characteristics are frequently used for 3D audio content creation, environmental acoustic effects, localization and acoustic scene analysis, etc.
Synergistic Learning of Lung Lobe Segmentation and Hierarchical Multi-Instance Classification for Automated Severity Assessment of COVID-19 in CT Images
Considering that only a few infection regions in a CT image are related to the severity assessment, we first represent each input image by a bag that contains a set of 2D image patches (with each cropped from a specific slice).
Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19
In this review paper, we thus cover the entire pipeline of medical imaging and analysis techniques involved with COVID-19, including image acquisition, segmentation, diagnosis, and follow-up.
Severity Assessment of Coronavirus Disease 2019 (COVID-19) Using Quantitative Features from Chest CT Images
Purpose: Using machine learning method to realize automatic severity assessment (non-severe or severe) of COVID-19 based on chest CT images, and to explore the severity-related features from the resulting assessment model.
Scene-Aware Audio Rendering via Deep Acoustic Analysis
We present a new method to capture the acoustic characteristics of real-world rooms using commodity devices, and use the captured characteristics to generate similar sounding sources with virtual models.
Sound Graphics Multimedia Audio and Speech Processing
Improving Reverberant Speech Training Using Diffuse Acoustic Simulation
We present an efficient and realistic geometric acoustic simulation approach for generating and augmenting training data in speech-related machine learning tasks.
Regression and Classification for Direction-of-Arrival Estimation with Convolutional Recurrent Neural Networks
We present a novel learning-based approach to estimate the direction-of-arrival (DOA) of a sound source using a convolutional recurrent neural network (CRNN) trained via regression on synthetic data and Cartesian labels.
Ranked #1 on
Direction of Arrival Estimation
on SOFA
(using extra training data)
