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This research aims to develop a Peruvian Sign Language (PSL) interpreter robot for children with hearing impairment, improving their integration in educational environments. Currently, 76% of public and 83% of private educational institutions are not prepared to serve deaf students, affecting 532,000 people with this disability. The design methodology was based on the German VDI 2206 standard, which guides the development of mechatronic systems for effective integration of mechanics, electronics and software. In addition, the high-level language Python was used. As a result, an eye- catching robot with a friendly face on the screen was developed. The robot uses a camera to recognise the signs and a Raspberry Pi to process the information, transcribing the signs into text, which is displayed on the screen along with a smiley face, making the interaction more child-friendly. By testing the system with 100 recognitions for each letter, an 86% accuracy rate was obtained in the overall recognition, indicating that the system is efficient. In conclusion, the simulations conducted indicate that the robot can translate sign language into speech, allowing for greater inclusion and participation of students with hearing disabilities and facilitating their learning and communication.

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Design and Development of a Peruvian Sign Language Interpreter Robot for Hearing-Impaired Children Using Artificial Intelligence

  • 会议论文

  • 发表日期：

    2026年

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  • Orlando Mark Alarcon Medina,
  • Yadhira S. Valenzuela Lino

摘要

This research aims to develop a Peruvian Sign Language (PSL) interpreter robot for children with hearing impairment, improving their integration in educational environments. Currently, 76% of public and 83% of private educational institutions are not prepared to serve deaf students, affecting 532,000 people with this disability. The design methodology was based on the German VDI 2206 standard, which guides the development of mechatronic systems for effective integration of mechanics, electronics and software. In addition, the high-level language Python was used. As a result, an eye- catching robot with a friendly face on the screen was developed. The robot uses a camera to recognise the signs and a Raspberry Pi to process the information, transcribing the signs into text, which is displayed on the screen along with a smiley face, making the interaction more child-friendly. By testing the system with 100 recognitions for each letter, an 86% accuracy rate was obtained in the overall recognition, indicating that the system is efficient. In conclusion, the simulations conducted indicate that the robot can translate sign language into speech, allowing for greater inclusion and participation of students with hearing disabilities and facilitating their learning and communication.