When I was heading ML at Skit.ai (2018-2024), our team worked on Spoken Language Understanding. Here are the team's publications:
- Rajaa, Shangeth (2023) "Improving End-to-End SLU performance with Prosodic Attention and Distillation", in Proc. Interspeech 2023
- Rajaa, Shangeth and Anandan, Kriti and Dalmia, Swaraj and Gupta, Tarun and Chng, Eng Siong (2023-06-04) "Improving Spoken Language Identification with Map-Mix", in ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
- Sahu, Surya Kant (2022) "On The Diversity of ASR Hypotheses In Spoken Language Understanding", in I Can’t Believe It’s Not Better Workshop: Understanding Deep Learning Through Empirical Falsification
- Sahu, Surya Kant (2022-11) "TaskMix: Data Augmentation for Meta-Learning of Spoken Intent Understanding", in Findings of the Association for Computational Linguistics: AACL-IJCNLP 2022
- Ganesan, Karthik and Bamdev, Pakhi and B, Jaivarsan and Venugopal, Amresh and Tushar, Abhinav (2021-08) "N-Best ASR Transformer: Enhancing SLU Performance using Multiple ASR Hypotheses", in Association for Computational Linguistics
During my MS (2016-2018), I worked part time in Reich Lab on Infectious Disease Epidemiology. Here are some items from that time:
- Reich, Nicholas G. and McGowan, Craig J. and Yamana, Teresa K. and Tushar, Abhinav and Ray, Evan L. and Osthus, Dave and Kandula, Sasikiran and Brooks, Logan C. and Crawford-Crudell, Willow and Gibson, Graham Casey (2019) "A collaborative multi-model ensemble for real-time influenza season forecasting in the US", in bioRxiv
- Reich, Nicholas G. and McGowan, Craig J. and Yamana, Teresa K. and Tushar, Abhinav and Ray, Evan L. and Osthus, Dave and Kandula, Sasikiran and Brooks, Logan C. and Crawford-Crudell, Willow and Gibson, Graham Casey (2019) "Accuracy of real-time multi-model ensemble forecasts for seasonal influenza in the US", in PLoS computational biology
- Reich, Nicholas G. and Brooks, Logan C. and Fox, Spencer J. and Kandula, Sasikiran and McGowan, Craig J. and Moore, Evan and Osthus, Dave and Ray, Evan L. and Tushar, Abhinav and Yamana, Teresa K. and Biggerstaff, Matthew and Johansson, Michael A. and Rosenfeld, Roni and Shaman, Jeffrey (2019-02-19) "A collaborative multiyear, multimodel assessment of seasonal influenza forecasting in the United States", in Proceedings of the National Academy of Sciences
- Reich, Nicholas G. and Brooks, Logan and Fox, Spencer and Kandula, Sasikiran and McGowan, Craig and Moore, Evan and Osthus, Dave and Ray, Evan and Tushar, Abhinav and Yamana, Teresa (2018) "Forecasting seasonal influenza in the US: A collaborative multi-year, multi-model assessment of forecast performance", in bioRxiv
- Tushar, Abhinav and Reich, Nicholas G. (2017-05-10) "flusight: interactive visualizations for infectious disease forecasts", in Journal of Open Source Software
Then here are some minor work during my Bachelor studies (2012-2016):
- Tushar, Abhinav (2016-09-24) "Making Sense of Hidden Layer Information in Deep Networks by Learning Hierarchical Targets", in arXiv
- Tushar, Abhinav and Dahiya, Abhinav (2015-11-05) "Comparing Writing Styles using Word Embedding and Dynamic Time Warping", in arXiv
- Tushar, Abhinav and Pillai, Gopinatha Nath (2015) "Extreme Learning ANFIS for classification problems", in 2015 1st International Conference on Next Generation Computing Technologies (NGCT)