Call for Papers:Vol.11 Issue.3

Submission
Last date		 28-Jun-2025
Acceptance Status In One Day
Paper Publish In Two Days
Submit ManuScript

News & Updates

Submit Article

Dear Authors, Article publish in our journal for Volume-11,Issue-3. For article submission on below link: Submit Manuscript


Join As Board

Dear Reviewer, You can join our Reviewer team without given any charges in our journal. Submit Details on below link: Join As Board


Paper Publication Charges

IJARIIE APP
Download Android App

For Authors

Archives

IJARIIE Board

Downloads

Android App

Download IJARIIE APP

Authors

Title: :  Feature Extraction Using Multi-modal Convolution Neural Network for Optical Speech Recognition
PaperId: :  9653
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 5 Issue 2 2019
DUI:    16.0415/IJARIIE-9653
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
GOKUL RAJES PSRM Institute of Science and Technology
Sayantan Chatterjee SRM Institute of Science and Technology
N SRICHARAN PHANINDRASRM Institute of Science and Technology
Kaustubh NarkhedeSRM Institute of Science and Technology
Saksham AlagSRM Institute of Science and Technology

Abstract

Electronics and Communication Engineering
CNN-convolutional neural network, HMM- Hidden Markov model, GMM- Gaussian Markov Model, and Architecture
This column orates the difficulties of continuous speech recognition system from optical information only, without using audio signal. Our method combines a video camera and an ultrasound imagining system for simultaneously detecting the speaker’s lips and the mobility of our tongue. We considered the usage of convolution neural network (CNN) to elicit the optical features directly from the basic ultrasound and optical images. We want to introduce variant architectures among which is a multimodal CNN processing jointly the two optical modalities together with an HMM-GMM decoder, the CNN type approach suppresses our earlier baseline based on principal component analysis. Notably, the recognition efficiency is 4 % lower than which was obtained decoding audio signal which makes it better for practical optical speech recognition system.

Citations

Copy and paste a formatted citation or use one of the links to import into a bibliography manager and reference.

IJARIIE GOKUL RAJES P, Sayantan Chatterjee , N SRICHARAN PHANINDRA, Kaustubh Narkhede, and Saksham Alag. "Feature Extraction Using Multi-modal Convolution Neural Network for Optical Speech Recognition" International Journal Of Advance Research And Innovative Ideas In Education Volume 5 Issue 2 2019 Page 476-480
MLA GOKUL RAJES P, Sayantan Chatterjee , N SRICHARAN PHANINDRA, Kaustubh Narkhede, and Saksham Alag. "Feature Extraction Using Multi-modal Convolution Neural Network for Optical Speech Recognition." International Journal Of Advance Research And Innovative Ideas In Education 5.2(2019) : 476-480.
APA GOKUL RAJES P, Sayantan Chatterjee , N SRICHARAN PHANINDRA, Kaustubh Narkhede, & Saksham Alag. (2019). Feature Extraction Using Multi-modal Convolution Neural Network for Optical Speech Recognition. International Journal Of Advance Research And Innovative Ideas In Education, 5(2), 476-480.
Chicago GOKUL RAJES P, Sayantan Chatterjee , N SRICHARAN PHANINDRA, Kaustubh Narkhede, and Saksham Alag. "Feature Extraction Using Multi-modal Convolution Neural Network for Optical Speech Recognition." International Journal Of Advance Research And Innovative Ideas In Education 5, no. 2 (2019) : 476-480.
Oxford GOKUL RAJES P, Sayantan Chatterjee , N SRICHARAN PHANINDRA, Kaustubh Narkhede, and Saksham Alag. 'Feature Extraction Using Multi-modal Convolution Neural Network for Optical Speech Recognition', International Journal Of Advance Research And Innovative Ideas In Education, vol. 5, no. 2, 2019, p. 476-480. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Feature_Extraction_Using_Multi_modal_Convolution_Neural_Network_for_Optical_Speech_Recognition_ijariie9653.pdf (Accessed : 01 August 2020).
Harvard GOKUL RAJES P, Sayantan Chatterjee , N SRICHARAN PHANINDRA, Kaustubh Narkhede, and Saksham Alag. (2019) 'Feature Extraction Using Multi-modal Convolution Neural Network for Optical Speech Recognition', International Journal Of Advance Research And Innovative Ideas In Education, 5(2), pp. 476-480IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Feature_Extraction_Using_Multi_modal_Convolution_Neural_Network_for_Optical_Speech_Recognition_ijariie9653.pdf (Accessed : 01 August 2020)
IEEE GOKUL RAJES P, Sayantan Chatterjee , N SRICHARAN PHANINDRA, Kaustubh Narkhede, and Saksham Alag, "Feature Extraction Using Multi-modal Convolution Neural Network for Optical Speech Recognition," International Journal Of Advance Research And Innovative Ideas In Education, vol. 5, no. 2, pp. 476-480, Mar-App 2019. [Online]. Available: https://ijariie.com/AdminUploadPdf/Feature_Extraction_Using_Multi_modal_Convolution_Neural_Network_for_Optical_Speech_Recognition_ijariie9653.pdf [Accessed : 01 August 2020].
Turabian GOKUL RAJES P, Sayantan Chatterjee , N SRICHARAN PHANINDRA, Kaustubh Narkhede, and Saksham Alag. "Feature Extraction Using Multi-modal Convolution Neural Network for Optical Speech Recognition." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 5 number 2 (01 August 2020).
Vancouver GOKUL RAJES P, Sayantan Chatterjee , N SRICHARAN PHANINDRA, Kaustubh Narkhede, and Saksham Alag. Feature Extraction Using Multi-modal Convolution Neural Network for Optical Speech Recognition. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2019 [Cited : 01 August 2020]; 5(2) : 476-480. Available from: https://ijariie.com/AdminUploadPdf/Feature_Extraction_Using_Multi_modal_Convolution_Neural_Network_for_Optical_Speech_Recognition_ijariie9653.pdf
BibTex EndNote RefMan RefWorks

Number Of Downloads


Last download on 8/1/2020 5:27:14 AM

Save in Google Drive

Similar-Paper

TitleArea of ResearchAuther NameAction
SOLAR WIRELESS ELECTRIC VEHICLE USING CHARGING SYSTEMElectronic and communication Hima J Download
Literature Review on Fibre Bragg Grating Sensors: Principles, Fabrication Techniques, Applications, and Future ProspectsElectronics and Communication Engineering Yashaswini D Download
Literature Survey on Smart Optical Fiber based Respiratory Monitoring systemElectronics and communication engineering Sai Priyanka A M Download
An loT Based Novel Approach to Health Emergency Management Through Real-Time Data Acquisition and AnalysisHealth sectorDr Siddesh G K Download
DESIGN AND DEVELOPMENT OF RIVER SURFACE CLEANING ROBOT USING IOTElectronics and communication engineeringBALAJI B R Download
A Solar Powered Wireless Power Transfer for Electric Vehicle (EV) ChargingElectronics and Communication EngineeringDr. Siddesh G K Download
AI-XRAY: AUTOMATED LUNG CANCER AND PNEUMONIA DETECTIONElectronics and communication engineeringYASHASWINI H M Download
Predictive Health Monitoring for Proactive Public Safety and ManagementElectronics and Communication EngineeringROOPA G D Download
IMPROVING BRAIN CANCER DETECTION THROUGH AI DRIVEN OBJECT RECOGNAISATIONElectronic and communication Parvathi CM Download
IOT BASED SMART FOOTWEAR FOR WOMEN & CHILDEREN SECURITYElectronics & CommunicationNandini G R Download
Smart Pesticide Sprayer Robot Using IOT In Agriculture FieldEletronics and Communication EngineeringMadhukeshava M Download
Evaluation of LoRa Based Air Pollution Monitoring SystemElectronic and Communication EngineeringSATHISH H Download
SMART CROP MONITORING SYSTEM AND IOTElectronics and Communication EngineeringSangeetha M R Download
Design of a IoT-based Water Harvesting, Moisture Monitoring, and Crop Monitoring System for Precision AgricultureElectronics and communication engineeringDeepthi T R Download
SMART GLOVES FOR SPEECH IMPAIRED PEOPLESELECTRONICS AND COMMUNICATION ENGINEERINGSudharshan M K Download
12