5 citations · 15 across the 9 of their papers we have counts for
9 papers
Synthesizing Sentiment-Controlled Feedback For Multimodal Text and Image Data
Puneet Kumar, Sarthak Malik, Balasubramanian Raman +1
The ability to generate sentiment-controlled feedback in response to multimodal inputs comprising text and images addresses a critical gap in human-computer interaction. This capab…
Interpretable Multimodal Emotion Recognition using Facial Features and Physiological Signals
Puneet Kumar, Xiaobai Li
This paper aims to demonstrate the importance and feasibility of fusing multimodal information for emotion recognition. It introduces a multimodal framework for emotion understandi…
Interpretable Multimodal Emotion Recognition using Hybrid Fusion of Speech and Image Data
Puneet Kumar, Sarthak Malik, Balasubramanian Raman
This paper proposes a multimodal emotion recognition system based on hybrid fusion that classifies the emotions depicted by speech utterances and corresponding images into discrete…
VISTANet: VIsual Spoken Textual Additive Net for Interpretable Multimodal Emotion Recognition
Puneet Kumar, Sarthak Malik, Balasubramanian Raman +1
This paper proposes a multimodal emotion recognition system, VIsual Spoken Textual Additive Net (VISTANet), to classify emotions reflected by input containing image, speech, and te…
Affective Feedback Synthesis Towards Multimodal Text and Image Data
Puneet Kumar, Gaurav Bhat, Omkar Ingle +2
In this paper, we have defined a novel task of affective feedback synthesis that deals with generating feedback for input text & corresponding image in a similar way as humans resp…
Region extraction based approach for cigarette usage classification using deep learning
Anshul Pundhir, Deepak Verma, Puneet Kumar +1
This paper has proposed a novel approach to classify the subjects' smoking behavior by extracting relevant regions from a given image using deep learning. After the classification,…
Interpretable Image Emotion Recognition: A Domain Adaptation Approach Using Facial Expressions
Puneet Kumar, Balasubramanian Raman
This paper proposes a feature-based domain adaptation technique for identifying emotions in generic images, encompassing both facial and non-facial objects, as well as non-human co…
End-to-end Triplet Loss based Emotion Embedding System for Speech Emotion Recognition
Puneet Kumar, Sidharth Jain, Balasubramanian Raman +2
In this paper, an end-to-end neural embedding system based on triplet loss and residual learning has been proposed for speech emotion recognition. The proposed system learns the em…
Fast Griffin Lim based Waveform Generation Strategy for Text-to-Speech Synthesis
Ankit Sharma, Puneet Kumar, Vikas Maddukuri +5
The performance of text-to-speech (TTS) systems heavily depends on spectrogram to waveform generation, also known as the speech reconstruction phase. The time required for the same…