[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117977-en":3,"doc-seo-117977-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},117977,3848291630094,"Emma Wilson","https://eur-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45",8,"Research & Report","Face Emotion Recognition Based on Machine Learning - A Review","Machine learning and information fusion enable computers to detect, understand, and evaluate emotions more effectively, driving growing interest in emotion identification. Researchers leverage facial expressions, words, body language, and posture, while acknowledging that the first approaches can be constrained by intentional or unintentional suppression of true feelings. This paper reviews feature extraction methods, classification models such as k-nearest neighbor, naive Bayes, support vector machine, and random forest, and summarizes state-of-the-art findings, key obstacles, and future directions for emotion-recognition algorithms.","International Journal of Informatics, Information System and Computer Engineering  \nFace Emotion Recognition Based on Machine Learning: A Review  \nAdnan Mohsin Abdulazeez *, Zainab Salih Ageed **  \n* Technical Informatics., College of Akre, Duhok Polytechnic University, Duhok, Iraq  \n** College of Science, Computer Science Dept., Nawroz University, Duhok, Iraq  \n*[Corresponding Email: Adnan.mohsin@dpu.krd.edu](Corresponding Email: Adnan.mohsin@dpu.krd.edu)  \n\n| A B S T R A C T S\u003Cbr>Computers can now detect, understand, and evaluate emotions thanks to recent developments in machine learning and information fusion. Researchers across various sectors are increasingly intrigued by emotion identification, utilizing facial expressions, words, body language, and posture as means of discerning an individual's emotions. Nevertheless, the effectiveness of the first three methods may be limited, as individuals can consciously or unconsciously suppress their true feelings. This article explores various feature extraction techniques, encompassing the development of machine learning classifiers like k-nearest neighbour, naive Bayesian, support vector machine, and random forest, in accordance with the established standard for emotion recognition. The paper has three primary objectives: firstly, to offer a comprehensive overview of effective computing by outlining essential theoretical concepts; secondly, to describe in detail the state-of-the-art in emotion recognition at the moment; and thirdly, to highlight important findings and conclusions from the literature, with an emphasis on important obstacles and possible future paths, especially in the creation of stateof-the-art machine learning algorithms for the identification of emotions.\u003Cbr>© 2021 Tim Konferensi UNIKOM | A R T I C L E I N F O |\n| --- | --- |\n|  | Article History:\u003Cbr>Received 01 Dec 2023 Revised 27 Dec 2023\u003Cbr>Accepted 05 Jan 2024\u003Cbr>Available online 17 Jan 2024 Publication Date 01 Jun 2024\u003Cbr>Keywords: Technology, Information System, Computer Science |\n\n1. INTRODUCTION  \nDespite their best efforts, humans cannot fully suppress emotions, as some researchers argue that emotions are inherent abilities. Emotion detection, an automated technique for determining an individual's affective state, is becoming more and more important in the field of human-computer interaction (HCI) for a variety of applications, such as automobile safety (Hudlicika & Broekens, 2009) . Unfortunately, most modern HCI systems lack emotional intelligence, rendering them incapable of processing or understanding emotional data and making decisions based on such information (Newell & M. Marabelli, 2015) . Typically, emotions are assessed by analyzing patterns of facial expressions, head movements, eyelid movements, or a combination of these factors. While the visual sense of facial emotions is valuable for emotion identification, it is not always sufficient (Vankalayapati et al., 2011) . In advanced intelligent systems, addressing the disconnect between humans and machines is crucial. A system that cannot recognize human affective states is prone to inadequate responses to those states. Therefore, it is crucial to train machines in interpreting and understanding human emotional states (Amanoul et al., 2021) . Asa result, the development of a reliable, accurate, flexible, and resilient emotion identification system becomes imperative for successful implementation in intelligent Human-Computer Interaction (HCI) . With the overarching goal of instilling machines with emotions, an increasing number of researchers in artificial intelligence (AI) have explored affective computing, particularly emotion recognition, establishing it as an emerging and promising area of study  \n(Kratzwald et al. 2018) . Numerous studies on emotion recognition in audiovisual formats have been conducted over the years. The literature generally exhibits three primary methods: visualbased, audio-visual, and audio-based approaches. Early r","cbCaikxcfrGuk9KQ","https://ap.wps.com/l/cbCaikxcfrGuk9KQ","pdf",795735,1,35,"English","en",105,"# Introduction\n# Background Theory","[{\"question\":\"What is the main goal of face emotion recognition in human-computer interaction?\",\"answer\":\"It aims to determine an individual's affective state so intelligent HCI systems can process emotional data and make more appropriate decisions.\"},{\"question\":\"Which methods does the paper discuss for building emotion recognition systems?\",\"answer\":\"It reviews feature extraction techniques and machine learning classifiers including k-nearest neighbor, naive Bayes, support vector machine, and random forest.\"},{\"question\":\"What limitations are noted in emotion recognition using facial, word, or posture-related cues?\",\"answer\":\"The effectiveness may be limited because people can consciously or unconsciously suppress their true feelings, weakening the observable signals.\"}]","Face Emotion Recognition Based on Machine Learning - A Review | PDF",1785680607,88,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":28},"face-emotion-recognition-based-on-machine-learning-a-review","",{"@graph":36,"@context":86},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/face-emotion-recognition-based-on-machine-learning-a-review/117977/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05","2026-08-02",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What is the main goal of face emotion recognition in human-computer interaction?","Question",{"text":76,"@type":77},"It aims to determine an individual's affective state so intelligent HCI systems can process emotional data and make more appropriate decisions.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"Which methods does the paper discuss for building emotion recognition systems?",{"text":81,"@type":77},"It reviews feature extraction techniques and machine learning classifiers including k-nearest neighbor, naive Bayes, support vector machine, and random forest.",{"name":83,"@type":74,"acceptedAnswer":84},"What limitations are noted in emotion recognition using facial, word, or posture-related cues?",{"text":85,"@type":77},"The effectiveness may be limited because people can consciously or unconsciously suppress their true feelings, weakening the observable signals.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":46,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":46,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":46,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":46,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":46,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":46,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]