E. Darren Ellis
Department of Computer and Electrical Engineering University of Tennessee, Knoxville Tennessee 37996
(Submitted: 09 May 2001)
This project entails the design of a speaker recognition code using MATLAB. Signal processing in the time and frequency domain yields a powerful method for analysis. MATLAB's built in functions for frequency domain analysis as well as its straightforward programming interface makes it an ideal tool for speech analysis projects. For the current project, experience was gained in general MATLAB programming and the manipulation of time domain and frequency domain signals. Speech editing was performed as well as degradation of signals by the application of Gaussian noise. Background noise was successfully removed from a signal by the application of a 3rd order Butterworth filter. A code was then constructed to compare the pitch and formant of a known speech file to 83 unknown speech files and choose the top twelve matches. I. INTRODUCTION
Development of speaker identification systems began as early as the 1960s with exploration into voiceprint analysis, where characteristics of an individual's voice were thought to be able to characterize the uniqueness of an individual much like a fingerprint. The early systems had many flaws and research ensued to derive a more reliable method of predicting the correlation between two sets of speech utterances. Speaker identification research continues today under the realm of the field of digital signal processing where many advances have taken place in recent years. In the current design project a basic speaker identification algorithm has been written to sort through a list of files and choose the 12 most likely matches based on the average pitch of the speech utterance as well as the location of the formants in the frequency domain representation. In addition, experience has been gained in basic filtering of high frequency noise...