Relevant bibliographies by topics / Indian sign language (ISL)

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Indian sign language (ISL)'

Author: Grafiati
Published: 4 June 2025
Last updated: 15 July 2025

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Journal articles on the topic "Indian sign language (ISL)"

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Shinde, Aditya. "Indian Sign Language Detection." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 01 (2025): 1–9. https://doi.org/10.55041/ijsrem41093.

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- The communication gap remains one of the most significant barriers between individuals with hearing and speech impairments and the broader society. This project addresses this challenge by developing a real-time Indian Sign Language (ISL) detection system that leverages computer vision and machine learning techniques. By capturing hand gestures from video input, the system translates these movements into text or speech, enabling effective communication between ISL users and those unfamiliar with the language. Additionally, the system incorporates text-to-speech functionality, ensuring a seam
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Mishra, Ravita, Gargi Angne, Nidhi Gawde, Preeti Khamkar, and Sneha Utekar. "SignSpeak: Indian Sign Language Recognition with ML Precision." Indian Journal Of Science And Technology 18, no. 8 (2025): 620–34. https://doi.org/10.17485/ijst/v18i8.4049.

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Objectives: To develop an accessible educational platform for Indian Sign Language (ISL) recognition, bridging communication gaps using advanced machine learning techniques, and promoting inclusivity for the hearing-impaired community. Methods: The study utilized Random Forest for classifying ISL letters and numbers with 1200 images per class and Long Short-Term Memory (LSTM)/Large Language Model (LLM) for gesture-based word and sentence recognition using 120 custom images. Feedback from Jhaveri Thanawala School for the Deaf validated the approach. Findings: The Random Forest model achieved 99
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Preeti Jain, Prof. "Healthcare Application Using Indian Sign Language." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem50261.

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Abstract - The absence of standardized and easily available technology solutions for people with disabilities—especially those who use Indian Sign Language (ISL) to access vital services like healthcare—means that there are still significant communication hurdles in India. Unlike American Sign Language (ASL), which is mostly one-handed, ISL relies on intricate two-handed motions, which creates unique difficulties for software-based interpretation systems. The lack of extensive, standardized ISL datasets, which are essential for developing precise machine learning and gesture recognition models
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Shinde, Aditya. "Enhanced Indian Sign Language Detection." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem49874.

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Abstract - The communication problem involving members of society who have speech and hearing impairments is still not fully resolved. In an earlier study, we created a real-time Indian Sign Language (ISL) recognition system which uses LSTM architecture for sequential gesture recognition. The focus of this paper is on further improving this system by changing the architecture from LSTM to CNN to enhance spatial feature extraction and overall system performance. Using a more comprehensive ISL dataset, we trained and tested the model and added new advanced preprocessing techniques such as Gaussi
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Aadhya, Satrasala, and al. et. "Indian Sign Language Translator Using CNN." International Journal of Computational Learning & Intelligence 4, no. 4 (2025): 792–98. https://doi.org/10.5281/zenodo.15279424.

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This paper main focus is to create a real-time Indian Sign Language (ISL) translator designed to overcome the gap between the deaf and hard-of-hearing population and the hearing population. By leveraging computer vision techniques and machine learning models, the system can accurately recognize a wide range of ISL gestures and translate them into corresponding text outputs in English.  The application is intended to facilitate seamless communication, enhancing accessibility in various settings such as education, healthcare, and daily interactions. This solution aims to foster greater incl
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Wankhade, Vaishnavi. "Indian Sign Language Detection using Machine Learning." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem30798.

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Indian Sign Language (ISL) serves as a primary means of communication for millions of hearing-impaired individuals in India. However, the lack of comprehensive tools for interpreting ISL poses significant challenges in facilitating effective communication and integration of the deaf community into society. This research paper explores the advancements, challenges, and potential applications of Indian Sign Language detection technology. It provides an overview of existing techniques for ISL detection, including computer vision-based approaches and wearable devices. Additionally, the paper discu
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Patole, Piyush, Mihir Sarawate, and Krushna Joshi. "A Communication Translator Interface for Sign Language Interpretation." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (2023): 4546–58. http://dx.doi.org/10.22214/ijraset.2023.52325.

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Abstract: Sign language is an essential means of communication for deaf and hard-of-hearing individuals. However, unlike spoken languages which have a universal language, every country has its own native sign language. In India, the Indian Sign Language (ISL) is used. This survey aims to provide an overview of the recognition and translation of essential Indian sign language. While significant research has been conducted in American Sign Language (ASL), the same cannot be said for Indian Sign Language due to its unique characteristics. The proposed method focuses on designing a tool for transl
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Ravita, Mishra, Angne Gargi, Gawde Nidhi, Khamkar Preeti, and Utekar Sneha. "SignSpeak: Indian Sign Language Recognition with ML Precision." Indian Journal of Science and Technology 18, no. 8 (2025): 620–34. https://doi.org/10.17485/IJST/v18i8.4049.

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<strong>Objectives:</strong>&nbsp;To develop an accessible educational platform for Indian Sign Language (ISL) recognition, bridging communication gaps using advanced machine learning techniques, and promoting inclusivity for the hearing-impaired community.&nbsp;<strong>Methods:</strong>&nbsp;The study utilized Random Forest for classifying ISL letters and numbers with 1200 images per class and Long Short-Term Memory (LSTM)/Large Language Model (LLM) for gesture-based word and sentence recognition using 120 custom images. Feedback from Jhaveri Thanawala School for the Deaf validated the approa
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Snehal, Pawar, Salunke Pragati, Mhasavade Arati, Bhutkar Aishwaraya, and R. Pathak K. "Real Time Identification of American Sign Language for Deaf and Dumb Community." Advancement in Image Processing and Pattern Recognition 2, no. 3 (2020): 1–7. https://doi.org/10.5281/zenodo.3600015.

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<em>The only way for deaf and dumb for communication is based on sign language which involves hand gestures. In this system, we are working on the American Sign Language (ASL) dataset (A-Z), (0-9) and word alphabet identification escort by our word identification dataset of Indian Sign Language (ISL). Sign data samples to be making our system more faultless, error free, and unambiguous with help of Convolutional Neural Network (CNN). Today, much research has been going on the field of sign language recognition but existing study failed to develop trust full communication interpreter. The motiv
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Pradnya D. Bormane. "Indian Sign Language Recognition: Support Vector Machine Approach." Advances in Nonlinear Variational Inequalities 27, no. 3 (2024): 716–27. http://dx.doi.org/10.52783/anvi.v27.1438.

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Indian Sign Language (ISL) is the primary form of communication for the dumb and deaf community in India. Recognizing Indian Sign Language plays an imperative part in promoting communication rights, social inclusion and equality for deaf people, while also contributing to technological advancement and cultural diversity. System’s ability to automatically recognize ISL signs could significantly improve community interactions between deaf and people with hearing loss. The objective of this research is to design a system that can accurately recognize and interpret Indian Sign language (ISL), ther
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Dissertations / Theses on the topic "Indian sign language (ISL)"

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Mudduluru, Sravani. "Indian Sign Language Numbers Recognition using Intel RealSense Camera." DigitalCommons@CalPoly, 2017. https://digitalcommons.calpoly.edu/theses/1815.

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The use of gesture based interaction with devices has been a significant area of research in the field of computer science since many years. The main idea of these kind of interactions is to ease the user experience by providing high degree of freedom and provide more interactive way of communication with the technology in a natural way. The significant areas of applications of gesture recognition are in video gaming, human computer interaction, virtual reality, smart home appliances, medical systems, robotics and several others. With the availability of the devices such as Kinect, Leap Motion
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McKay-Cody, Melanie Raylene 1962. "Plains Indian Sign Language: A comparative study of alternate and primary signers." Thesis, The University of Arizona, 1997. http://hdl.handle.net/10150/278590.

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An extensive literature review has been undertaken to create an accurate portrayal of North American Indian Sign Language as used by both deaf and hearing American Indians. Historical accounts are stressed as the primary source for understanding the extent of signed language use among the American Indians of North American and its decline to the present status as an endangered language. This sign language has functioned in two significant ways: (1) primarily (for hearing tribal members) as an alternative to the spoken language and (2) as a primary, or first language for deaf tribal members. It
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Singhal, Shikha, and Shalakha Singhal. "Hand Gesture Recognition using Depth Data for Indian Sign Language." Thesis, 2013. http://ethesis.nitrkl.ac.in/5033/1/109EC0244.pdf.

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It is hard for most people who are not familiar with a sign language to communicate without an interpreter. Thus, a system that transcribes symbols in sign languages into plain text can help with real-time communication, and it may also provide interactive training for people to learn a sign language. A sign language uses manual communication and body language to convey meaning. The depth data for five different gestures corresponding to alphabets Y, V, L, S, I was obtained from online database. Each segmented gesture is represented by its timeseries curve and feature vector is extracted from
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Books on the topic "Indian sign language (ISL)"

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People's Linguistic Survey of India, ed. Indian sign language(s). Orient Blackswan Private Limited, 2014.

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Liptak, Karen. North American Indian sign language. F. Watts, 1992.

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professeur, DuBois Daniel, ed. Indian signals and sign language. Bonanza Books, 1985.

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Liptak, Karen. North American Indian sign language. Scholastic, 1995.

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Fronval, George. Indian signals and sign language. Wings Books, 1994.

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Liptak, Karen. North American Indian sign language. Scholastic, 1995.

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Liptak, Karen. North American Indian sign language. F. Watts, 1990.

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Olsen, Madeline. Native American sign language. Scholastic, 2005.

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Museum of the Plains Indian and Crafts Center (U.S.), ed. Plains Indian sign language: A memorial to the Conference, September 4-6, 1930, Browning, Montana. U.S. Dept. of the Interior, Indian Arts and Crafts Board, Museum of the Plains Indian and Crafts Center, 1997.

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McAuley, Skeet. Sign language: Contemporary Southwest native America. Aperture, 1989.

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Book chapters on the topic "Indian sign language (ISL)"

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Ghosh, Ananya, and Parthiban Krishnamoorthy. "FedXAI-ISL: Explainable Artificial Intelligence-Based Federated Model in Recognition and Community Decentralized Learning of Indian Sign Language." In Innovative Computing and Communications. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-3588-4_32.

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Mishra, Vidyanand, Jayant Uppal, Honey Srivastav, Divyanshi Agarwal, and Harshit. "Sign Language Recognition for Indian Sign Language." In Advances in Data-Driven Computing and Intelligent Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-3250-4_12.

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Katoch, Shivansh, and Krishan Kumar. "Indian Sign Language Bilateral Translator." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-60935-0_67.

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Suvagiya, Pratik H., Chintan M. Bhatt, and Ritesh P. Patel. "Indian Sign Language Translator Using Kinect." In Advances in Intelligent Systems and Computing. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0135-2_2.

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Mounin, Georges. "An Analysis of Indian Sign Language." In Semiotic Praxis. Springer US, 1985. http://dx.doi.org/10.1007/978-1-4684-4829-0_5.

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Santhosh, K. S., Sanjay K. Hoysala, D. R. Srihari, Suhith Shekar Chandra, and A. N. Krishna. "Gesture Recognition of Indian Sign Language." In Lecture Notes in Networks and Systems. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0980-0_3.

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Mallikarjuna Swamy, N., H. S. Sumanth, Keerthi, C. Manjunatha, and R. Sumathi. "Indian Sign Language Detection Using YOLOv3." In Lecture Notes in Electrical Engineering. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9885-9_13.

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Puri, Sudaksh, Meghna Sinha, Sanjana Golaya, and Ashwani Kumar Dubey. "Indian Sign Language Recognition Using Python." In Advances in Intelligent Systems and Computing. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4367-2_41.

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Sharma, Deepika, Bhaskar Chaurasia, Rohit Majumder, Nilima Patil, Sanika Khankale, and Aditya Tyagi. "Mudra talk: Indian sign language translator." In Intelligent Computing and Communication Techniques. CRC Press, 2025. https://doi.org/10.1201/9781003635680-112.

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Mehrotra, Kapil, Atul Godbole, and Swapnil Belhe. "Indian Sign Language Recognition Using Kinect Sensor." In Lecture Notes in Computer Science. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20801-5_59.

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Conference papers on the topic "Indian sign language (ISL)"

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Venkadesh, P., G. Jelin Taric, P. Mary Mariyal, S. V. Divya, S. Danumithra, and K. Anuranjani. "SignChatAI-Generative AI for Deaf-and-Mute Community using Indian Sign Language(ISL)." In 2024 International Conference on Computing and Intelligent Reality Technologies (ICCIRT). IEEE, 2024. https://doi.org/10.1109/iccirt59484.2024.10921817.

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Praharsha, Chittathuru Himala, and Alwin Poulose. "ISLC SCNN: Indian Sign Language Classification System Using Shallow Convolution Neural Networks." In 2024 IEEE International Conference on Contemporary Computing and Communications (InC4). IEEE, 2024. http://dx.doi.org/10.1109/inc460750.2024.10649345.

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Siddharth, S., R. Jayashree, and K. N. Shwetha. "Indian Sign Language Recognition System." In 2024 11th International Conference on Soft Computing & Machine Intelligence (ISCMI). IEEE, 2024. https://doi.org/10.1109/iscmi63661.2024.10851588.

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Kumar, Sujay Grama Suresh, and Jad Abbass. "Enhancing Sign Language Communication: Advanced Gesture Recognition Models for Indian Sign Language." In 2025 International Research Conference on Smart Computing and Systems Engineering (SCSE). IEEE, 2025. https://doi.org/10.1109/scse65633.2025.11031017.

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S, Gayathri, Madhumitta P, Usha Nandhini G, and Anuradha M. "Indian Sign Language Classification Using Transfer Learning." In 2024 International Conference on Computing, Sciences and Communications (ICCSC). IEEE, 2024. https://doi.org/10.1109/iccsc62048.2024.10830325.

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M, Ahmed Aslam, Mohamed Aabidh A, and N. Sabiyath Fatima. "Real-Time Indian Sign Language Recognition & Multilingual Sign Generation." In 2025 Third International Conference on Augmented Intelligence and Sustainable Systems (ICAISS). IEEE, 2025. https://doi.org/10.1109/icaiss61471.2025.11041851.

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Kumar, Chevella Anil, V. Sagar Reddy, Nainika Kandarpa, and Pallavi Sharma. "Smart IoT System for Indian Sign Language Translator." In 2024 Second International Conference on Intelligent Cyber Physical Systems and Internet of Things (ICoICI). IEEE, 2024. http://dx.doi.org/10.1109/icoici62503.2024.10696760.

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Joshi, Abhinav, Romit Mohanty, Mounika Kanakanti, et al. "iSign: A Benchmark for Indian Sign Language Processing." In Findings of the Association for Computational Linguistics ACL 2024. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.findings-acl.643.

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Ojaswee, R. Sreemathy, Mousami Turuk, Jayashree Jagdale, and Mohammad Anish. "Indian Sign Language Recognition Using Video Vision Transformer." In 2024 3rd International Conference for Advancement in Technology (ICONAT). IEEE, 2024. https://doi.org/10.1109/iconat61936.2024.10774678.

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B, Chempavathy, Syam Dev R. S, Rohit Karmakar, Sidhu I. S, Nishanth V, and P. Sumanthraj. "Multi-Modal ISL-Speech: A Real-Time Neural Architecture for Sign Language Translation to Natural Language." In 2024 4th International Conference on Ubiquitous Computing and Intelligent Information Systems (ICUIS). IEEE, 2024. https://doi.org/10.1109/icuis64676.2024.10866815.

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