Deep learning techniques—R-CNN to mask R-CNN: a survey P Bharati, A Pramanik Computational Intelligence in Pattern Recognition: Proceedings of CIPR 2019 …, 2020 | 263* | 2020 |
End-to-End Native Language Identification Using a Modified Vision Transformer (ViT) from L2 English Speech K Pipariya, D Pramanik, P Bharati, S Chandra, SKD Mandal International Conference on Speech and Computer, 529-538, 2023 | | 2023 |
ATT: Adversarial Trained Transformer for Speech Enhancement A Aitawade, P Bharati, S Chandra, GS Prasad, D Pramanik, PS Khadse, ... International Conference on Speech and Computer, 258-270, 2023 | | 2023 |
Speech Enhancement Using LinkNet Architecture A Patel, GS Prasad, S Chandra, P Bharati, SK Das Mandal International Conference on Speech and Computer, 245-257, 2023 | | 2023 |
Towards The Development Of Accent Conversion Model For (L1) Bengali Speaker Using Cycle Consistent Adversarial Network (Cyclegan) S Chandra, P Bharati, SKD Mandal 2022 25th Conference of the Oriental COCOSDA International Committee for the …, 2022 | | 2022 |
Speech Enhancement: Traditional and Deep Learning Techniques GS Prasad, A Patel, P Bharati, S Chandra, N Ghosh, SKD Mandal | | |
Automatic Deep Neural Network-Based Segmental Pronunciation Error Detection of L2 English Speech (L1 Bengali) P Bharati, S Chandra, SKD Mandal | | |