Master ’ S Thesis 2003 : 138 Civ

ii ACKNOWLEDGEMENTS A number of people have been involved in my work and I wish to express my warmest gratitude to everyone who supported and help me in different ways. First of all I am deeply grateful to my husband Jianlin Shi. Without his understanding, valuable advice and patience, my thesis could not have been attempted and completed. I want to express my heartfelt thanks to my supervisor Emma-Christin Lönnroth for her persistent help, skilful and excellent guidance and positive encouragement. I really appreciated her enthusiasm and valuable suggestions during the whole period that I studied at the Division of Industrial Ergonomics of M.Sc. program. Thanks to Professor Houshang Shahnavaz for introducing me into ergonomic field and valuable instructions. My sincerely gratitude also goes to my friends Haoxue and Wu peng for their kind helps and discussions on everything inside as well as outside the scientific world. I would like to express my thanks to all of my colleagues in M.Sc. program for their help and friendship. I wish to express my gratitude to my parent for their great support. Finally, I dedicate this thesis in the honour of my dear husband Jianlin. Abstract In the last few decades, the computer keyboards input device has received much attention in the past and is believed by many to be a prime factor in the etiology of upper extremity musculoskeletal disorders. And wide rang of voice input systems are proposed to allow persons to operate a computer without using a keyboard or mouse. This thesis reviewed both of acoustic–only and bimodal voice recognition system and compared their recognition accuracy in simulated noisy environments. Then, the voice recognition technique is adopted in keyboard design to fulfil keyboard ergonomic demands. Finally, the value analysis was performed to evaluate the redesigned voice input keyboards. The experiment results demonstrate, compared to conventional acoustic only based speech recognition, bimodal speech recognition scheme has a much improved recognition accuracy and using the visual features allows the development of a more practical and real-time recognition system. Through the redesigned voice input keyboard, computer users can get their hand free completely and partly at their own will, by which they are away from the upper extremity musculoskeletal disorders risk and vocal strain.