Papers by Chandra Kiran Reddy Evuru
ProSE: Diffusion Priors for Speech Enhancement (2025.naacl-long)
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Sonal Kumar, Sreyan Ghosh, Utkarsh Tyagi, Anton Jeran Ratnarajah, Chandra Kiran Reddy Evuru, Ramani Duraiswami, Dinesh Manocha
| Challenge: | deterministic deep learning models have been used for speech enhancement, but generative models have shown promise. |
| Approach: | They propose a method to apply diffusion probabilistic models to speech enhancement using priors in a latent space. |
| Outcome: | The proposed method achieves state-of-the-art performance on synthetic and real-world datasets while consuming less computational costs. |
DALE: Generative Data Augmentation for Low-Resource Legal NLP (2023.emnlp-main)
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Sreyan Ghosh, Chandra Kiran Reddy Evuru, Sonal Kumar, S Ramaneswaran, S Sakshi, Utkarsh Tyagi, Dinesh Manocha
| Challenge: | DALE addresses the challenges existing frameworks pose in generating effective data augmentations of legal documents. |
| Approach: | They propose a generative Data Augmentation framework for low-resource legal NLP that exploits domain-specific language characteristics of templated legal documents to mask collocated spans of text. |
| Outcome: | The proposed framework outperforms baseline frameworks on 13 datasets and 4 low-resource settings. |