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Text-Based Emotion Recognition Using Deep Learning Approach

Santosh Kumar Bharti, S Varadhaganapathy, Rajeev Kumar Gupta, Prashant Kumar Shukla, Mohamed Bouye, Simon Karanja Hingaa, Amena Mahmoud, Vijay Kumar
2022 Computational Intelligence and Neuroscience  
In this article, we have proposed a hybrid (machine learning + deep learning) model to identify emotions in text.  ...  However, emotion detection in text is a tedious task as cues are missing, unlike in speech, such as tonal stress, facial expression, pitch, etc.  ...  Figure 3 : 3 Figure 3: Six types of emotions in our Dataset. Figure 5 : 5 Figure 5: GRU model to detect emotions from text. Figure 6 : 6 Figure 6: Bi-GRU model to detect emotions from Text.  ... 
doi:10.1155/2022/2645381 pmid:36052029 pmcid:PMC9427219 fatcat:4fntq6utczdyxm2j3o4qilajda

Computational approaches for emotion detection in text

Haji Binali, Chen Wu, Vidyasagar Potdar
2010 4th IEEE International Conference on Digital Ecosystems and Technologies  
This paper presents emotion theories that provide a basis for emotion models. It shows how these models have been used by discussing computational approaches to emotion detection.  ...  We propose a hybrid based architecture for emotion detection. The SVM algorithm is used for validating the proposed architecture and achieves a prediction accuracy of 96.43% on web blog data.  ...  However, there is a paucity of research in emotion detection from text in comparison to the other areas of emotion detection [14, 15] .  ... 
doi:10.1109/dest.2010.5610650 fatcat:zxokpjxafbauvdso6ggnhmqp2q

A Novel Semantic Approach for Intelligent Response Generation using Emotion Detection Incorporating NPMI Measure

Naresh Kumar D, Gerard Deepak, A Santhanavijayan
2020 Procedia Computer Science  
Hence, there is a need for a proper methodology for the interpretation of emotions based on both text and speech.  ...  In order to accomplish this task, a light weight computational linguistic semantic approach has been proposed for detecting emotions and generating response incorporating NPMI and NAVA words, bridging  ...  Various audio interactions have been studied for the implementation of the model. Bandhakavi et al., [24] have devised a model for emotion detection from text.  ... 
doi:10.1016/j.procs.2020.03.320 fatcat:vlqel53uyveidgtoup3jcqra7q

A Novel Approach for Detecting Emotion in Text

Sudhanshu Prakash Tiwari, M. Vijaya Raju, Gurbakash Phonsa, Deepak Kumar Deepu
2016 Indian Journal of Science and Technology  
Objectives: In this paper, we present an experiment, which concerned with detection of emotion class at sentence level.  ...  There is a large annotated data set which manually classified a sentence beyond six basic emotions: love, joy, anger, sadness, fear, surprise.  ...  But the field emotion detection from text needs much improvement. There are many models to detect the emotion from text.  ... 
doi:10.17485/ijst/2016/v9i29/88211 fatcat:7bzcoj37obcflaxxm2e5qw5iry

Sarcasm Detection using Deep Learning

Seema Kedar, Et. al.
2021 Turkish Journal of Computer and Mathematics Education  
In this paper, we have implemented sarcasm detection based upon difference and similarity between facial emotion of the person and sentiment of his verbally conveyed message.  ...  It is becoming a trend in current society to use complex and indirect statements for communication which includes metaphorical language, proverbs and other similar forms.  ...  Accuracy for sentiment analysis from text is 82.4%, for facial emotion recognition is 92.4% and for sarcasm detection is 80.4%.  ... 
doi:10.17762/turcomat.v12i1s.1558 fatcat:vth53llnsfe7fbnw2zmad7hgqq

AI Cannot Understand Memes: Experiments with OCR and Facial Emotions

Ishaani Priyadarshini, Chase Cotton
2022 Computers Materials & Continua  
We use a combination of Optical Character Recognition techniques like Tesseract, Pixel Link, and East Detector to extract text from the memes, and machine learning algorithms like Convolutional Neural  ...  Networks (CNN), Region-based Convolutional Neural Networks (RCNN), and Transfer Learning with pre-trained denseNet for assessing the textual and facial emotions combined.  ...  Funding Statement: The authors received no specific funding for this study. Conflicts of Interest: The authors declare that they have no conflicts of interest to report regarding the present study.  ... 
doi:10.32604/cmc.2022.019284 fatcat:bqtsviatqfezni3wcoesq5xn4i

A Novel Method to Evaluate Students Sentiments from Twitter Messages

2019 International journal of recent technology and engineering  
A hybrid-based approach which contains lexical and learning based approaches will be used to handle the twitter-based data and to predict the emotions of a student.  ...  Emotions can be analyzed mainly through many ways like facial features, audio signals and text messages.  ...  The first mechanism gathered huge streams of text data from twitter and created a model to train from the information or keywords in the text message.  ... 
doi:10.35940/ijrte.c5667.098319 fatcat:nanrso635jbh7gd6jgwyz5tcja

Text and Voice Input to Emotional Analysis for AI Clients

Simran Bhake
2020 International Journal for Research in Applied Science and Engineering Technology  
The detection of emotion from sentence is the most important part of emotion analysis. Emotion detection from text consists of extraction of emotional class method.  ...  Detecting Emotional state of a person can be challenging but also very crucial. Emotions can be detected through various ways from human i.e facial expressions, gestures, speech and written text.  ...  In this approach, instead of detecting predefined emotional keywords from text, a probabilistic affinity is assigned for a specific emotion to arbitrary words.  ... 
doi:10.22214/ijraset.2020.1042 fatcat:xu6b7hsf6befrgxhlo2iaiinkq

Keyword Based Emotion Word Ontology Approach for Detecting Emotion Class from Text

2016 International Journal of Science and Research (IJSR)  
This paper is mainly focused on an overview of emotion detection from text and describes the emotion detection methods.  ...  Limitations of these emotion recognition methods are presented in this paper and also, address the text normalization using different handling techniques for both plaint text and short messaging language  ...  This assigns a probabilistic affinity for a particular emotion to arbitrary words rather than detecting predefined emotional keywords from text.  ... 
doi:10.21275/v5i5.nov163818 fatcat:kre7biccezccnbqhflhreyezeq

ArmanEmo: A Persian Dataset for Text-based Emotion Detection [article]

Hossein Mirzaee
2022 arXiv   pre-print
With the recent proliferation of open textual data on social media platforms, Emotion Detection (ED) from Text has received more attention over the past years.  ...  ArmanEmo is publicly available for non-commercial use at https://github.com/Arman-Rayan-Sharif/arman-text-emotion.  ...  Acknowledgement The authors would like to thank Arman Rayan Sharif for providing required financial and computational resources in this project.  ... 
arXiv:2207.11808v1 fatcat:rhtbidg3pndu3arf343tjhii5y

Emotion Detection From Text Documents

Shiv Naresh Shivhare, Sri Khetwat Saritha
2014 International Journal of Data Mining & Knowledge Management Process  
At the next step paper also proposed a new architecture for recognizing emotions from text document.  ...  A sufficient amount of work has been done by researchers to detect emotions from facial and audio information whereas recognizing emotions from textual data is still a fresh and hot research area.  ...  A proposed architecture which contains the emotion ontology and emotion detector algorithm is explained in Section 3. Based on this, a system is designed for emotion detection from text documents.  ... 
doi:10.5121/ijdkp.2014.4605 fatcat:e6mtevnp2zfyhbl3tqo22sdx4u

Emotion Detection from Text [article]

Shiv Naresh Shivhare, Saritha Khethawat
2012 arXiv   pre-print
Emotion Detection in text documents is essentially a content - based classification problem involving concepts from the domains of Natural Language Processing as well as Machine Learning.  ...  In this paper emotion recognition based on textual data and the techniques used in emotion detection are discussed.  ...  A sufficient amount of work has been done by researchers to detect emotion from facial and audio information whereas recognizing emotions from textual data is still a fresh and hot research area.  ... 
arXiv:1205.4944v1 fatcat:qdz5w3ngmrasngwyzwomt2wlki

Sentiment-Aware Word Embedding for Emotion Classification

Xingliang Mao, Shuai Chang, Jinjing Shi, Fangfang Li, Ronghua Shi
2019 Applied Sciences  
We propose sentiment-aware word embedding for emotional classification, which consists of integrating sentiment evidence within the emotional embedding component of a term vector.  ...  Extensive results on several machine learning models show that the proposed methods can improve the accuracy of emotion classification tasks.  ...  Algorithm 1 sentiment-aware word embedding for emotion classification Input: a set of unclassified text documents Output: a set of classified text documents 1 for each doc ∈ corpus do 2 for each term ∈  ... 
doi:10.3390/app9071334 fatcat:hbjukgmeojemzk5y3gdi2rddwe

Hybrid Deep Learning Model for Fake News Detection in Social Networks (Student Abstract)

Bibek Upadhayay, Vahid Behzadan
2022 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
In this work, we propose a novel hybrid deep learning model for fake news detection that augments the semantic characteristics of the news with features extracted from the structure of the dissemination  ...  To this end, we first extend the LIAR dataset by integrating sentiment and affective features to the data, and then use a BERT-based model to obtain a representation of the text.  ...  Hybrid Model Our proposed method is a hybrid of both style-based detection and network-based detection. This hybrid process flow diagram is shown in Fig1.  ... 
doi:10.1609/aaai.v36i11.21670 fatcat:prmadmigbfaynhtlwovmqqe24m

A Hybrid System for Online Detection of Emotional Distress [chapter]

Tim M. H. Li, Michael Chau, Paul W. C. Wong, Paul S. F. Yip
2012 Lecture Notes in Computer Science  
In the light of this situation, we present a hybrid system based on affect analysis for mining emotional distress tendencies from publicly available blogs to identify needy people in order to provide timely  ...  We describe the system architecture with a hand-crafted model at a fine level of detail.  ...  A scoring system is also incorporated in the model. The model provides a new direction for document classification from a sentence-level prospective. Fig. 1.  ... 
doi:10.1007/978-3-642-30428-6_6 fatcat:3ixj5hcegneixjzqtysm46ixuy
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