Date Approved
4-2018
Graduate Degree Type
Thesis
Degree Name
Engineering (M.S.E.)
Degree Program
School of Engineering
First Advisor
Nicholas Baine
Second Advisor
Samhita Rhodes
Third Advisor
Robert Bossemeyer
Academic Year
2017/2018
Abstract
Speech recognition is a very useful technology because of its potential to develop applications, which are suitable for various needs of users. This research is an attempt to enhance the performance of a speech recognition system by combining the visual features (lip movement) with audio features. The results were calculated using utterances of numerals collected from participants inclusive of both male and female genders. Discrete Cosine Transform (DCT) coefficients were used for computing visual features and Mel Frequency Cepstral Coefficients (MFCC) were used for computing audio features. The classification was then carried out using Support Vector Machine (SVM). The results obtained from the combined/fused system were compared with the recognition rates of two standalone systems (Audio only and visual only).
ScholarWorks Citation
Acharya, Vikrant Satish, "Fusion of Audio and Visual Information for Implementing Improved Speech Recognition System" (2018). Masters Theses. 884.
https://scholarworks.gvsu.edu/theses/884
