E. Darren Ellis
Department of Computer and Electrical Engineering University of Tennessee, Knoxville
(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.
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... [continues]
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