[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121848-en":3,"doc-seo-121848-105":30,"detail-sidebar-cat-0-en-105":91},{"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":4,"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},121848,3848291630094,"Emma Wilson","https://eur-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45",8,"Research & Report","GESTURE RECOGNITION OF MACHINE LEARNING AND CONVOLUTIONAL NEURAL NETWORK METHODS FOR KAZAKH SIGN LANGUAGE","Machine learning and neural networks have gained broad public interest due to rapid advances that improve computer recognition of objects, sounds, texts, and other data. This progress in computer vision supports increasingly sophisticated models for recognizing hand gestures and enabling more natural human-computer interaction. The study examines popular hand-gesture recognition models—CNN, LSTM, and SVM—comparing approaches, processing time, and training data requirements. Experiments train the models for Kazakh sign language recognition using the dactyl alphabet and evaluate performance through detailed method descriptions, effectiveness, and recorded experimental results.","DOI: 10. 37943/15LPCU4095  \n© Samat Mukhanov, Raissa Uskenbayeva, Young Im Cho, Kabyl Dauren, Les Nurzhan, Maqsat Amangeldi  \n85  \nDOI: 10.37943/15LPCU4095  \nSamat Mukhanov*  \nMaster of Technical Sciences, senior-lecturer, Department of Computer Engineering  \n[s.mukhanov@iitu.edu.kz](s.mukhanov@iitu.edu.kz), [orcid.org/0000-0001-8761-4272](orcid.org/0000-0001-8761-4272)[ ](orcid.org/0000-0001-8761-4272)International Information Technology University, Almaty, Kazakhstan  \nRaissa Uskenbayeva  \nDoctor of technical science, professor, Head of Institute of Automation, and Information Technologies  \n[r.k.uskenbayeva@satbayev.university](r.k.uskenbayeva@satbayev.university), [orcid.org/0000-0002-8499-2101](orcid.org/0000-0002-8499-2101)[ ](orcid.org/0000-0002-8499-2101)Satbayev University, Almaty, Kazakhstan  \nYoung Im Cho  \nPhD, professor  \n[yicho@gachon.ac.kr](yicho@gachon.ac.kr), [orcid.org/0000-0003-0184-7599](orcid.org/0000-0003-0184-7599)  \nFaculty of Computer Engineering Gachon University, Seoul, South Korea  \nKabyl Dauren  \nMaster student  \n[d_kabyl@kbtu.kz](d_kabyl@kbtu.kz), [orcid.org/0009-0005-4837-8728](orcid.org/0009-0005-4837-8728)  \nKazakh British Technical University, Almaty, Kazakhstan  \nLes Nurzhan  \nMaster student  \n[38530@iitu.edu.kz](38530@iitu.edu.kz), [orcid.org/0009-0008-2909-3606](orcid.org/0009-0008-2909-3606)  \nInternational Information Technology University, Almaty, Kazakhstan  \nMaqsatAmangeldi  \nMaster student  \n[38517@iitu.edu.kz](38517@iitu.edu.kz), [orcid.org/0009-0002-0899-2975](orcid.org/0009-0002-0899-2975)  \nInternational Information Technology University, Almaty, Kazakhstan  \nGESTURE RECOGNITION OF MACHINE LEARNING AND CONVOLUTIONAL NEURAL NETWORK METHODS FOR KAZAKH SIGN LANGUAGE  \nAbstract: Recently, there has been a growing interest in machine learning and neural networks among the public, largely due to advancements in technology which have led to improved methods of computer recognition of objects, sounds, texts, and other data types. Asa result, human-computer interactions are becoming more natural and comprehensible to the average person. The progress in computer vision has enabled the use of increasingly sophisticated models for object recognition in images and videos, which can also be applied to recognize hand gestures. In this research, popular hand gesture recognition models, such asthe Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and Support Vector Machine (SVM) were examined. These models vary in their approaches, processing time, and training data size. The important feature of this research work is the use of various machine learning algorithms and methods such as CNN, LSTM, and SVM. Experiments showed different results when training neural networks for sign language recognition in the Kazakh sign language based on the dactyl alphabet. This article provides a detailed description of each method, their respective purposes, and effectiveness in terms of performance and training. Numerous experimental results were recorded in a table, demonstrating the accuracy of rec  \nCopyright © 2023, Authors. This is an open access article under the Creative Commons CC BY-NC-ND license Received: 31.07.2023 Accepted: 13.09.2023 Published: 30.09.2023  \n86  \nScientific Journal of Astana IT University ISSN (P): 2707-9031 ISSN (E): 2707-904X VOLUME 15, SEPTEMBER 2023  \nognizing each gesture. Additionally, specific hand gestures were isolated for testing in front of the camera to recognize the gesture and display the result on the screen. An important feature was the use of mathematical formulas and functions to explain the working principle of the machine learning algorithm, as well as the logical scheme and structure of the LSTM algorithm.  \nKeywords: Hand gesture recognition; neural networks; CNN; LSTM; SVM.  \nIntroduction  \nAt present, Kazakhstan has a population of over 200,000 individuals who are unable to speak and more than 80,000 who are hearing-impaired. On a global scale,","cbCaihC66MVfnemP","https://ap.wps.com/l/cbCaihC66MVfnemP","pdf",3824419,1,16,"English","en",105,"# Introduction\n# Literature review and problem statement","[{\"question\":\"Which hand gesture recognition models are examined in the research?\",\"answer\":\"The research examines CNN, LSTM, and SVM models for hand gesture recognition in Kazakh sign language.\"},{\"question\":\"How is the Kazakh sign language dataset prepared for training and testing?\",\"answer\":\"Experiments train the models for recognition in Kazakh sign language based on the dactyl alphabet, and specific gestures are isolated for testing in front of the camera.\"},{\"question\":\"What factors are compared across the models?\",\"answer\":\"The models are compared by their approaches, processing time, and training data size, with effectiveness assessed via performance results.\"}]","GESTURE RECOGNITION OF MACHINE LEARNING AND CONVOLUTIONAL NEURAL NETWORK METHODS FOR KAZAKH SIGN LANGUAGE | PDF",1785807216,40,{"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":86,"head_meta":88,"extra_data":90,"updated_unix":28},"gesture-recognition-of-machine-learning-and-convolutional-neural-network-methods-for-kazakh-sign-language","",{"@graph":36,"@context":85},[37,54,68],{"@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/gesture-recognition-of-machine-learning-and-convolutional-neural-network-methods-for-kazakh-sign-language/121848/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Which hand gesture recognition models are examined in the research?","Question",{"text":75,"@type":76},"The research examines CNN, LSTM, and SVM models for hand gesture recognition in Kazakh sign language.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How is the Kazakh sign language dataset prepared for training and testing?",{"text":80,"@type":76},"Experiments train the models for recognition in Kazakh sign language based on the dactyl alphabet, and specific gestures are isolated for testing in front of the camera.",{"name":82,"@type":73,"acceptedAnswer":83},"What factors are compared across the models?",{"text":84,"@type":76},"The models are compared by their approaches, processing time, and training data size, with effectiveness assessed via performance results.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":29,"slug":118},7,"Healthcare","healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]