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Influence of delay time on regularity estimation for voice pathology detection
J A Gómez García1, J I Godino Llorente, G Castellanos Dominguez
1Bioengineering and Optoelectronics, Universidad Politécnica de Madrid, Spain. jorgomezg@unal.edu.co
Summary
Optimizing voice pathology detection requires careful parameter selection. This study reveals that choosing a delay time (τ) other than 1 improves the accuracy of nonlinear analysis for detecting voice disorders.
Area of Science:
- Biomedical Engineering
- Signal Processing
- Acoustics
Background:
- Nonlinear analysis is crucial for voice pathology detection, capturing complex signal dynamics.
- Traditional methods often use a fixed delay time (τ=1), potentially missing nonlinear characteristics.
Purpose of the Study:
- To investigate the impact of the delay time (τ) parameter on nonlinear regularity features for voice analysis.
- To determine if alternative τ values enhance the accuracy of automatic voice pathology detection.
Main Methods:
- Examined three methods for estimating delay time (τ): a baseline of 1, Average Mutual Information, and embedding window.
- Applied these τ estimations to regularity feature calculations for pathological voice samples.
Main Results:
- Results indicate that a delay time (τ) different from 1 can lead to improved accuracy in voice pathology detection.
- Non-unity τ values better capture the underlying nonlinearities present in voice signals.
Conclusions:
- The choice of delay time (τ) significantly influences the effectiveness of nonlinear analysis in voice pathology detection.
- Employing optimized τ values, beyond the conventional unity, is recommended for enhanced diagnostic accuracy.
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