Transign AI

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Transign AI

Dr.P.Sumathi, Head of Department, SNS College of Engineering , Coimbatore, India

Ms. Padmashri N, Supervisor, SNS College of Engineering , Coimbatore, India

Abinesh jino U P, Student, SNS College of Engineering , Coimbatore, India
Gopika M, Student, SNS College of Engineering , Coimbatore, India

Kaviya K, Student, SNS College of Engineering , Coimbatore, India

Megha M, Student, SNS College of Engineering , Coimbatore, India

Abstract - The project "Speech to Sign Language Converter" presents a user-friendly and inclusive solution aimed at bridging communication gaps for the hearing-impaired. Utilizing advanced speech-to-text algorithms, natural

language processing (NLP), and emotion recognition, the system converts spoken audio into Indian Sign Language (ISL) representations. A key feature is the integration of Google APIs to retrieve contextual images that enhance the expressiveness of the sign output. By embedding emotional cues within sign gestures, the system provides a more humanized and accurate communication experience. This paper outlines the technical framework, implementation methodology, and potential impact of this AI-powered assistive tool.

Keywords — Sign Language, Emotion Recognition, NLP, Google API, Speech to Text, Assistive Technology

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