most citedNaRLE: Natural Language Models using Reinforcement Learning with Emotion Feedback

2 citations · 2 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CL20212 cited

NaRLE: Natural Language Models using Reinforcement Learning with Emotion Feedback

Ruijie Zhou, Soham Deshmukh, Jeremiah Greer +1

Current research in dialogue systems is focused on conversational assistants working on short conversations in either task-oriented or open domain settings. In this paper, we focus…

eess.AS2021

Improving weakly supervised sound event detection with self-supervised auxiliary tasks

Soham Deshmukh, Bhiksha Raj, Rita Singh

While multitask and transfer learning has shown to improve the performance of neural networks in limited data settings, they require pretraining of the model on large datasets befo…

eess.AS2020

Interpreting glottal flow dynamics for detecting COVID-19 from voice

Soham Deshmukh, Mahmoud Al Ismail, Rita Singh

In the pathogenesis of COVID-19, impairment of respiratory functions is often one of the key symptoms. Studies show that in these cases, voice production is also adversely affected…

eess.AS2020

Detection of COVID-19 through the analysis of vocal fold oscillations

Mahmoud Al Ismail, Soham Deshmukh, Rita Singh

Phonation, or the vibration of the vocal folds, is the primary source of vocalization in the production of voiced sounds by humans. It is a complex bio-mechanical process that is h…

eess.AS2020

Multi-Task Learning for Interpretable Weakly Labelled Sound Event Detection

Soham Deshmukh, Bhiksha Raj, Rita Singh

Weakly Labelled learning has garnered lot of attention in recent years due to its potential to scale Sound Event Detection (SED) and is formulated as Multiple Instance Learning (MI…