most citedDeep Learning based Emotion Recognition System Using Speech Features and Transcriptions

56 citations · 59 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2019

Visual Context-aware Convolution Filters for Transformation-invariant Neural Network

Suraj Tripathi, Abhay Kumar, Chirag Singh

We propose a novel visual context-aware filter generation module which incorporates contextual information present in images into Convolutional Neural Networks (CNNs). In contrast…

eess.AS201956 cited

Deep Learning based Emotion Recognition System Using Speech Features and Transcriptions

Suraj Tripathi, Abhay Kumar, Abhiram Ramesh +2

This paper proposes a speech emotion recognition method based on speech features and speech transcriptions (text). Speech features such as Spectrogram and Mel-frequency Cepstral Co…

cs.IR20193 cited

From Fully Supervised to Zero Shot Settings for Twitter Hashtag Recommendation

Abhay Kumar, Nishant Jain, Suraj Tripathi +1

We propose a comprehensive end-to-end pipeline for Twitter hashtags recommendation system including data collection, supervised training setting and zero shot training setting. In…

cs.SD2019

Learning Discriminative features using Center Loss and Reconstruction as Regularizer for Speech Emotion Recognition

Suraj Tripathi, Abhiram Ramesh, Abhay Kumar +2

This paper proposes a Convolutional Neural Network (CNN) inspired by Multitask Learning (MTL) and based on speech features trained under the joint supervision of softmax loss and c…

cs.CV2019

Exploiting SIFT Descriptor for Rotation Invariant Convolutional Neural Network

Abhay Kumar, Nishant Jain, Chirag Singh +1

This paper presents a novel approach to exploit the distinctive invariant features in convolutional neural network. The proposed CNN model uses Scale Invariant Feature Transform (S…