5 papers
ML-Based Analysis to Identify Speech Features Relevant in Predicting Alzheimer's Disease
Yash Kumar, Piyush Maheshwari, Shreyansh Joshi +1
Alzheimer's disease (AD) is a neurodegenerative disease that affects nearly 50 million individuals across the globe and is one of the leading causes of deaths globally. It is proje…
Deep Neural Networks on EEG Signals to Predict Auditory Attention Score Using Gramian Angular Difference Field
Mahak Kothari, Shreyansh Joshi, Adarsh Nandanwar +2
Auditory attention is a selective type of hearing in which people focus their attention intentionally on a specific source of a sound or spoken words whilst ignoring or inhibiting…
Alzheimers Dementia Detection using Acoustic & Linguistic features and Pre-Trained BERT
Akshay Valsaraj, Ithihas Madala, Nikhil Garg +1
Alzheimers disease is a fatal progressive brain disorder that worsens with time. It is high time we have inexpensive and quick clinical diagnostic techniques for early detection an…
Vyākarana: A Colorless Green Benchmark for Syntactic Evaluation in Indic Languages
Rajaswa Patil, Jasleen Dhillon, Siddhant Mahurkar +3
While there has been significant progress towards developing NLU resources for Indic languages, syntactic evaluation has been relatively less explored. Unlike English, Indic langua…
CNRL at SemEval-2020 Task 5: Modelling Causal Reasoning in Language with Multi-Head Self-Attention Weights based Counterfactual Detection
Rajaswa Patil, Veeky Baths
In this paper, we describe an approach for modelling causal reasoning in natural language by detecting counterfactuals in text using multi-head self-attention weights. We use pre-t…