Musical timbre is inherently multidimensional and extremely complex in structure. For those reasons, timbre is an on-going research topic in areas such as computer science, psychology, music and engineering. Humans have the natural ability to segregate, identify and recognize sounds in a variety of situations - separated by a wall from the sound source, in a concert hall, within a noisy traffic environment or at a cocktail party. Although computer systems have been realized to determine ways of recognizing and identifying sounds with extracted features, none have come close to performing nearly as well as humans do. The robustness of computer systems degrades especially in uncontrolled or natural settings, where more than one sound source, distortions and aural distractions exist. Many questions remain unanswered: how and what kind of information does the brain actually receive from our auditory sensory organs; which features are critically important and which are redundant or even cause confusion in the recognition and identification process?

The timbre recognition process for computer systems may be basically divided into two parts. Firstly, the feature extraction part which extracts salient characteristics of an acoustic signal. Secondly, the recognition part which uses the extracted data for categorization, prediction and taxonomy. In this thesis I will concentrate on the feature extraction part. I have implemented and developed a number of algorithms that are useful in picking out acoustical characteristics of musical instruments. The purpose of the software is to give musicians and researchers a usable tool for exploration of timbral characteristics. The signal processing algorithms implemented in software were all realized in the Java programming environment. The system can be regarded as a GUI (graphical user interface) based frequency and time domain signal processing system, where timbral features are extracted and displayed visually for better understanding.

First and foremost, I thank Jon Appleton for giving me the opportunity to come to the Electro-Acoustic Music Program at Dartmouth and making my two years a challenging, memorable and exciting time. Many thanks to Larry Polanksy for his invaluable guidance, advice and the countless discussions. I am very grateful to Charlie Sullivan for his thoughtful and insightful critiques which have helped me tremendously in finishing the thesis. Thanks to Charles Dodge for introducing me to so many different facets of music I did not know existed, Douglas Repetto, Mary Roberts and Eric Lyon for their support. I would also like to thank Dee Copley for keeping it all together, Andrew, Iroro, Jonathan and Paul for letting me "multi-computer" all the time (well, most of the time).

I thank my parents and brothers for their unending encouragement and being the best teachers I have had. They have been there for me throughout the years, guided me and supported me with all the different (and sometimes strange) paths I had chosen.

Finally, I wish to thank Kyoung Hyun for her continual and unwavering support, understanding and love. It would have been very hard to reach this milestone without her - thank you.