34 citations · 72 across the 10 of their papers we have counts for
5 papers · 1 filter
Synthetic Wave-Geometric Impulse Responses for Improved Speech Dereverberation
Rohith Aralikatti, Zhenyu Tang, Dinesh Manocha
We present a novel approach to improve the performance of learning-based speech dereverberation using accurate synthetic datasets. Our approach is designed to recover the reverb-fr…
Reverberation as Supervision for Speech Separation
Rohith Aralikatti, Christoph Boeddeker, Gordon Wichern +2
This paper proposes reverberation as supervision (RAS), a novel unsupervised loss function for single-channel reverberant speech separation. Prior methods for unsupervised separati…
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…
Audio-Visual Decision Fusion for WFST-based and seq2seq Models
Rohith Aralikatti, Sharad Roy, Abhinav Thanda +4
Under noisy conditions, speech recognition systems suffer from high Word Error Rates (WER). In such cases, information from the visual modality comprising the speaker lip movements…
Global SNR Estimation of Speech Signals using Entropy and Uncertainty Estimates from Dropout Networks
Rohith Aralikatti, Dilip Margam, Tanay Sharma +2
This paper demonstrates two novel methods to estimate the global SNR of speech signals. In both methods, Deep Neural Network-Hidden Markov Model (DNN-HMM) acoustic model used in sp…