Language Interpreter and Speaker

Authors

  •   Ruchi Bari Student, Vidyavardhini College of Engineering and Technology, K.T. Marg, Vartak College Campus, Vasai Road (W), District Palghar, Vasai, Maharashtra - 401 202
  •   Mrunmayee Apte Student, Vidyavardhini College of Engineering and Technology, K.T. Marg, Vartak College Campus, Vasai Road (W), District Palghar, Vasai, Maharashtra - 401 202
  •   Aakanksha Mohite Student, Vidyavardhini College of Engineering and Technology, K.T. Marg, Vartak College Campus, Vasai Road (W), District Palghar, Vasai, Maharashtra - 401 202
  •   Sainath Patil Assistant Professor (Guide), Vidyavardhini College of Engineering and Technology, K.T. Marg, Vartak College Campus, Vasai Road (W), District Palghar, Vasai, Maharashtra - 401 202

DOI:

https://doi.org/10.17010/ijcs/2022/v7/i2/169682

Keywords:

AlexNet

, CNN (Convolution Neural Network), gTTS (google-text-to-speech), Image Processing

Publishing Chronology Manuscript Received

, February 20, 2022, Revised, March 8, Accepted, March 16, 2022. Date of Publication, April 5, 2022.

Abstract

Language Interpreter and Speaker is a device for identifying the language of the written image text and then converting the same text to speech format. This device would surely be useful for blind and visually impaired people. Language identification (LI) is the method in which we identify the natural language of the given content. It is the process of categorizing a document on the basis of its language. In this generation, we are heading towards a phase where computers would be capable of doing all things that humans can do. Recognition of language used is the initial requirement before reading or learning. To start with any of the tasks, humans first try to understand the task and then process the task. Similarly, for language identification, the machine needs to learn the language and once learning is complete, it should be able to recognize the language. The project is divided into three parts. Initially, the handwritten image text would be converted to normal text. In the second part, the language would be identified from the converted text and last, the text would be converted to audio format. This paper discusses the implementation of this idea, gives an approach to problems and challenges that we came across, and some solutions.

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Author Biographies

Ruchi Bari, Student, Vidyavardhini College of Engineering and Technology, K.T. Marg, Vartak College Campus, Vasai Road (W), District Palghar, Vasai, Maharashtra - 401 202

ORCID iD : https://orcid.orglOOOO·0002·9315-6674

Mrunmayee Apte, Student, Vidyavardhini College of Engineering and Technology, K.T. Marg, Vartak College Campus, Vasai Road (W), District Palghar, Vasai, Maharashtra - 401 202

ORCIDiD:https://orcid.orglOOOO·0002·0770-Q400

Aakanksha Mohite, Student, Vidyavardhini College of Engineering and Technology, K.T. Marg, Vartak College Campus, Vasai Road (W), District Palghar, Vasai, Maharashtra - 401 202

ORCID iD : https://orcid.orglOOOO·0002·1077-0100

Sainath Patil, Assistant Professor (Guide), Vidyavardhini College of Engineering and Technology, K.T. Marg, Vartak College Campus, Vasai Road (W), District Palghar, Vasai, Maharashtra - 401 202

ORCIDiD : https://orcid.orglOOOO-0002-8226-43895

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Published

2022-04-01

How to Cite

Bari, R., Apte, M., Mohite, A., & Patil, S. (2022). Language Interpreter and Speaker. Indian Journal of Computer Science, 7(2), 24–31. https://doi.org/10.17010/ijcs/2022/v7/i2/169682

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