Enhancing Communication Accessibility: A Deep Learning Approach to Gesture Recognition for the Deaf and Mute Community

被引:0
|
作者
Kandula, Ashok Reddy [1 ]
Ramachandran, Priya Darshini [1 ]
Tummalapalli, Nikhitha [1 ]
Tirukkovalluri, Krishna Priya [1 ]
Kothapalli, Kavya [1 ]
机构
[1] Seshadri Rao Gudlavalleru Engn Coll, Dept AI & DS, Gudlavalleru, India
关键词
Recurrent Neural Network; long short-term memory; OpenCV; Media pipe; Rectified Linear Unit; SoftMax; Adam Optimizer; Gesture Classification;
D O I
10.1109/ICPCSN62568.2024.00142
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Though human communication is crucial, individuals with physical obstacles like deafness and naivety frequently find it challenging to communicate effectively. Utilizing sign language can be a primitive component of communication among this group. This paper suggests a creative approach to closing the communication hole by engaging the comprehension of sign dialect without the prerequisite for people to memorize it. Tallying flag recording on webcams gives a successful and straightforward means of collecting data. These hand advancements are meticulously recorded and utilized as the primitive for planning and testing models. The credibility of pushing for inclusivity exists, as does the potential for making more effective communication channels that cater to assorted social classes. Sign tongue isn't a burdensome errand due to the effortlessness of this procedure, which makes communication less demanding. Through this unused approach, social instinct will progress through predominant communication, frequent understanding, and support among particular levels of society. In this way, this movement has the potential to begin noteworthy updates in interpersonal associations, develop inclusivity, and address existing boundaries for fruitful communication. This research work attempted it more than once and were attained a better accuracy of 90%.
引用
收藏
页码:842 / 849
页数:8
相关论文
共 50 条
  • [1] Deep Learning Approach for Hand Gesture Recognition: Applications in Deaf Communication and Healthcare
    Aurangzeb, Khursheed
    Javeed, Khalid
    Alhussein, Musaed
    Rida, Imad
    Haider, Syed Irtaza
    Parashar, Anubha
    CMC-COMPUTERS MATERIALS & CONTINUA, 2024, 78 (01): : 127 - 144
  • [2] Enhancing sign language recognition and accessibility for the deaf community in China
    Lai, Zhuiwen
    Huang, Zhengzong
    Wen, Ya
    Feng, Jinmei
    DISABILITY & SOCIETY, 2024,
  • [3] Hand Gesture Recognition towards Enhancing Accessibility
    Cardoso, Tiago
    Delgado, Joao
    Barata, Jose
    PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON SOFTWARE DEVELOPMENT AND TECHNOLOGIES FOR ENHANCING ACCESSIBILITY AND FIGHTING INFO-EXCLUSION, 2015, 67 : 419 - 429
  • [4] A Deep Learning Approach for Hybrid Hand Gesture Recognition
    Alonso, Diego G.
    Teyseyre, Alfredo
    Berdun, Luis
    Schiaffino, Silvia
    ADVANCES IN SOFT COMPUTING, MICAI 2019, 2019, 11835 : 87 - 99
  • [5] Hand Gesture Recognition for Deaf-Mute using Fuzzy-Neural Network
    Brando Villagomez, Emilio, III
    Addiezza King, Roxanne
    Ordinario, Mark Joshua
    Lazaro, Jose
    Villaverde, Jocelyn Flores
    2019 4TH IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS - ASIA (IEEE ICCE-ASIA 2019), 2019, : 30 - 33
  • [6] Silent no more: a comprehensive review of artificial intelligence, deep learning, and machine learning in facilitating deaf and mute communication
    Zaineldin, Hanaa
    Gamel, Samah A.
    Talaat, Fatma M.
    Aljohani, Mansourah
    Baghdadi, Nadiah A.
    Malki, Amer
    Badawy, Mahmoud
    Elhosseini, Mostafa A.
    ARTIFICIAL INTELLIGENCE REVIEW, 2024, 57 (07)
  • [7] Deep Learning Approach for Gesture Recognition on Millimeter-Wave Radar
    Liu, Jiang
    Liu, Yuming
    Wang, Yunxuan
    Chen, Yating
    Zhou, Tianxiang
    Huang, Yan
    2022 INTERNATIONAL CONFERENCE ON MICROWAVE AND MILLIMETER WAVE TECHNOLOGY (ICMMT), 2022,
  • [8] Research on Communication APP for Deaf and Mute People Based on Face Fmotion Recognition Technology
    Tao, Yuan
    Huo, Shihang
    Zhou, Wenyu
    PROCEEDINGS OF 2020 IEEE 2ND INTERNATIONAL CONFERENCE ON CIVIL AVIATION SAFETY AND INFORMATION TECHNOLOGY (ICCASIT), 2020, : 547 - 552
  • [9] Real-time Arabic avatar for deaf-mute communication enabled by deep learning sign language translation
    Talaat, Fatma M.
    El-Shafai, Walid
    Soliman, Naglaa F.
    Algarni, Abeer D.
    El-Samie, Fathi E. Abd
    Siam, Ali I.
    COMPUTERS & ELECTRICAL ENGINEERING, 2024, 119
  • [10] Deep Learning-Based Approach for Sign Language Gesture Recognition With Efficient Hand Gesture Representation
    Al-Hammadi, Muneer
    Muhammad, Ghulam
    Abdul, Wadood
    Alsulaiman, Mansour
    Bencherif, Mohammed A.
    Alrayes, Tareq S.
    Mathkour, Hassan
    Mekhtiche, Mohamed Amine
    IEEE ACCESS, 2020, 8 (08): : 192527 - 192542