A robust tool to compare pre- and post-surgical voice quality

Area of Science:

• Medical acoustics
• Speech pathology
• Signal processing

Background:

• Objective voice quality assessment is crucial for clinicians but often hindered by complex tools.
• Clinicians prefer a limited set of reliable voice parameters due to usability challenges.

Purpose of the Study:

• To develop and validate an automated, user-friendly tool for robust voice quality analysis.
• To simplify the assessment of key voice parameters for non-expert users.

Main Methods:

• Focus on robust, automatic evaluation of fundamental frequency (F0), jitter (J), Relative Average Perturbation (RAP), and formant frequencies.
• Employs adaptive estimation of signal frame lengths for high-resolution analysis.
• Analyzes only voiced segments of the signal, automatically handling various signal types and sampling frequencies.

Main Results:

• The developed tool provides automatic analysis of voice signals without manual user settings.
• Mean and standard deviation values for selected parameters are displayed.
• The system is validated on patients with vocal fold cysts and polyps.

Conclusions:

• The proposed tool offers a feasible solution for objective voice quality assessment, even for non-expert users.
• Its automated and simplified approach enhances clinical applicability for voice disorders.