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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM58053

A Real-Time Lip Reading to Speech Android Application for Mute

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM58053

Volume:

10 |

3 |

Mar 2026

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

PRS

Puppala Ramya Sri

DR

Dr.Mogili Ravinder

CA

Cheekati Abhinay

ND

Nagula Deekshitha

GP

Gourishetty Pavani

PA

Podeti Ajith

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Abstract

Communication is one of the basic needs for every human being. However, for those suffering from muteness, communicating in their daily lives is a significant challenge. For those who are not aware of existing solutions like sign language or communication through typing, this paper proposes a Real Time Lip Reading to Speech Android Application that uses Artificial Intelligence for converting lip movement into speech. The proposed application uses Android’s CameraX for video recording, MediaPipe for lip region detection, and TensorFlow Lite for offline deep learning model prediction. The predicted words are then converted into speech using Android’s Text-toSpeech (TTS). The proposed application is designed for offline video upload processing without requiring internet connectivity. The proposed system’s effectiveness in assisting communication for those suffering from muteness has been tested in experiments.

KEYWORDS

Lip Reading Visual Speech Recognition Computer Vision TensorFlow Lite MediaPipe Offline AI Android Application Assistive Technology

Cite This Article

Puppala Ramya Sri, Dr.Mogili Ravinder, Cheekati Abhinay, Nagula Deekshitha, Gourishetty Pavani, Podeti Ajith, "A Real-Time Lip Reading to Speech Android Application for Mute," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 3, Mar 2026.

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Publication Date

3/22/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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3

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5

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The authors declare no conflict of interest related to this research work.

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