Hardware implementation of a voice stress detection algorithm using empirical mode decomposition
- WCU Author/Contributor (non-WCU co-authors, if there are any, appear on document)
- Joshua Schwartz (Creator)
- Institution
- Western Carolina University (WCU )
- Web Site: http://library.wcu.edu/
- Advisor
- Robert Adams
Abstract: In previous research, using EMD for voice stress analysis showed promising results. The
original algorithm was developed in Matlab, utilizing many of its functions. The algorithm
decodes audio into a raw format sampling at 8k samples/sec. This signal array is then filtered
and centered about the x-axis and the local maxima and minima are determined.
Matlab’s built-in cubic spline interpolation function was then used to create the upper and
lower envelopes. The first Intrinsic Mode Function (IMF) is determined by calculating the
difference between the original signal and the mean of the envelopes. The algorithm continually
extracts IMFs starting with the highest frequency IMF until it extracts the last IMF.
The last IMF represents the frequency of the stress induced tremor in the subjects voice.
The successfulness of the algorithm was measured using a series of questions designed to
invoke a stress response concatenated with irrelevant questions designed not to invoke a
stress response. The difference between the tremor frequency related to the stressful and
non-stressful questions determines if a person may be being untruthful.
Hardware implementation of a voice stress detection algorithm using empirical mode decomposition
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Created on 4/1/2011
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Additional Information
- Publication
- Thesis
- Language: English
- Date: 2011
- Subjects
- Voice -- Psychological stress analysis
- Stress (Psychology) -- Measurement