%0 Journal Article
%T Noise Suppression in Tele-Lectures using Bi-Modal Feature Extraction
%A E.S.Selvakumar
%A S.Shanmuga Priya
%J International Journal of Computer Science and Network
%D 2013
%I IJCSN publisher
%X Automatic Speech Recognition (ASR) is an essential componentin many Human-Computer Interaction systems. A variety ofapplications in the field of ASR have reached high performancelevels but only for condition-controlled environments. In thisproject, we reduce the noise in the video lectures using bi-modalfeature extraction. Audio signal features need to be enhancedwith additional sources of complementary information toovercome problems due to large amounts of acoustic noise.Visual Information extracted from speaker¡¯s mouth region seemsto be promising and appropriate for giving audio-onlyrecognition a boost. Lip/Mouth detection and tracking combinedwith traditional Image Processing methods may offer a variety ofsolutions for the construction of the visual front-end schema.Furthermore, Audio and Visual stream fusion appears to be evenmore challenging and crucial for designing an efficient AVRecognizer. In this project, we investigate some problems in thefield of Audio-Visual Automatic Speech Recognition (AV-ASR)concerning visual feature extraction and audio-visual integrationto reduce noise in the video lectures.
%K ASR
%K Audio-visual automatic speech recognition
%K Feature extraction
%K Multi-stream HMM
%U http://ijcsn.org/IJCSN-2013/2-2/IJCSN-2013-2-2-64.pdf