| Multi-conditioning and data augmentation using generative noise model for speech emotion recognition in noisy conditions U Tiwari, M Soni, R Chakraborty, A Panda, SK Kopparapu ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 45 | 2020 |
| Audio-visual fusion for sentiment classification using cross-modal autoencoder SH Dumpala, I Sheikh, R Chakraborty, SK Kopparapu 32nd conference on neural information processing systems (NIPS 2018), 1-4, 2019 | 39 | 2019 |
| A Novel Data Representation for Effective Learning in Class Imbalanced Scenarios. SH Dumpala, R Chakraborty, SK Kopparapu, TCS Reseach IJCAI, 2100-2106, 2018 | 32 | 2018 |
| Calibration free meta learning based approach for subject independent EEG emotion recognition S Bhosale, R Chakraborty, SK Kopparapu Biomedical Signal Processing and Control 72, 103289, 2022 | 29 | 2022 |
| Sound-model-based acoustic source localization using distributed microphone arrays R Chakraborty, C Nadeu 2014 IEEE International Conference on Acoustics, Speech and Signal …, 2014 | 27 | 2014 |
| TCS-ILAB-MediaEval 2015: Affective Impact of Movies and Violent Scene Detection. R Chakraborty, AK Maurya, M Pandharipande, E Hassan, H Ghosh, ... MediaEval 1436, 2015 | 23 | 2015 |
| Deep encoded linguistic and acoustic cues for attention based end to end speech emotion recognition S Bhosale, R Chakraborty, SK Kopparapu ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 21 | 2020 |
| Analyzing emotion in spontaneous speech R Chakraborty, M Pandharipande, SK Kopparapu Springer Singapore, 2017 | 19 | 2017 |
| Knowledge-based framework for intelligent emotion recognition in spontaneous speech R Chakraborty, M Pandharipande, SK Kopparapu Procedia Computer Science 96, 587-596, 2016 | 19 | 2016 |
| An unsupervised frame selection technique for robust emotion recognition in noisy speech M Pandharipande, R Chakraborty, A Panda, SK Kopparapu 2018 26th European signal processing conference (EUSIPCO), 2055-2059, 2018 | 15 | 2018 |
| Identification of dementia using audio biomarkers R Chakraborty, M Pandharipande, C Bhat, SK Kopparapu arXiv preprint arXiv:2002.12788, 2020 | 14 | 2020 |
| Sentiment analysis using imperfect views from spoken language and acoustic modalities I Sheikh, SH Dumpala, R Chakraborty, SK Kopparapu Proceedings of grand challenge and workshop on human multimodal language …, 2018 | 13 | 2018 |
| Front-End Feature Compensation and Denoising for Noise Robust Speech Emotion Recognition. R Chakraborty, A Panda, M Pandharipande, S Joshi, SK Kopparapu INTERSPEECH, 3257-3261, 2019 | 12 | 2019 |
| Robust front-end processing for emotion recognition in noisy speech M Pandharipande, R Chakraborty, A Panda, SK Kopparapu 2018 11th International Symposium on Chinese Spoken Language Processing …, 2018 | 12 | 2018 |
| Detection and positioning of overlapped sounds in a room environment R Chakraborty, C Nadeu, T Butko Thirteenth Annual Conference of the International Speech Communication …, 2012 | 12 | 2012 |
| Dementia classification using acoustic descriptors derived from subsampled signals A Triapthi, R Chakraborty, SK Kopparapu 2020 28th European signal processing conference (EUSIPCO), 91-95, 2021 | 11 | 2021 |
| Mining call center conversations exhibiting similar affective states R Chakraborty, M Pandharipande, SK Kopparapu Proceedings of the 30th Pacific Asia Conference on Language, Information and …, 2016 | 10 | 2016 |
| Improved speech emotion recognition using error correcting codes R Chakraborty, SK Kopparapu 2016 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), 1-6, 2016 | 9 | 2016 |
| Contrastive Learning of Cough Descriptors for Automatic COVID-19 Preliminary Diagnosis. S Bhosale, U Tiwari, R Chakraborty, SK Kopparapu Interspeech, 946-950, 2021 | 8 | 2021 |
| k-FFNN: A priori knowledge infused Feed-forward Neural Networks SH Dumpala, R Chakraborty, SK Kopparapu arXiv preprint arXiv:1704.07055, 2017 | 8 | 2017 |
