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Speech to text translation enabling multilingualism.

Bano, Shahana; Jithendra, Pavuluri; Niharika, Gorsa Lakshmi; Sikhi, Yalavarthi


Pavuluri Jithendra

Gorsa Lakshmi Niharika

Yalavarthi Sikhi


Speech acts as a barrier to communication between two individuals and helps them in expressing their feelings, thoughts, emotions, and ideologies among each other. The process of establishing a communicational interaction between the machine and mankind is known as Natural Language processing. Speech recognition aids in translating the spoken language into text. We have come up with a Speech Recognition model that converts the speech data given by the user as an input into the text format in his desired language. This model is developed by adding Multilingual features to the existent Google Speech Recognition model based on some of the natural language processing principles. The goal of this research is to build a speech recognition model that even facilitates an illiterate person to easily communicate with the computer system in his regional language.


BANO, S., JITHENDRA, P., NIHARIKA, G.L. and SIKHI, Y. 2020. Speech to text translation enabling multilingualism. In Proceedings of the 2020 International conference for innovation in technology (INOCON 2020), 6-8 November 2020, Bangluru, India. Piscataway: IEEE [online]. Available from:

Conference Name 2020 International conference for innovation in technology (INOCON 2020)
Conference Location Bangluru, India
Start Date Nov 6, 2020
End Date Nov 8, 2020
Acceptance Date Jul 30, 2020
Online Publication Date Jan 1, 2021
Publication Date Dec 31, 2020
Deposit Date Sep 20, 2023
Publicly Available Date Sep 20, 2023
Publisher Institute of Electrical and Electronics Engineers (IEEE)
ISBN 9781728197456
Keywords Speech recognition; Natural language processing; Language translation; Machine learning
Public URL


BANO 2020 Speech to text translation (AAM) (337 Kb)

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