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Updated: Jun 25, 2025

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A Novel Algorithm Application in Vocal Signals Processing.

Giuseppe Timpano1, Patrizia Vizza1

  • 1Department of Surgical and Medical Sciences, Magna Graecia University, Italy.

Studies in Health Technology and Informatics
|May 24, 2024
PubMed
Summary
This summary is machine-generated.

The Goertzel Algorithm (GA) offers a more efficient method for analyzing vocal signals in dysphonia evaluation than the standard Fast Fourier Transform (FFT). This technique improves the distinction between healthy and pathological voices, aiding clinical monitoring.

Keywords:
Goertzel algorithmSignal AnalysisVocal signal

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Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Speech Science

Background:

  • Dysphonia evaluation relies on accurate vocal signal analysis.
  • Current methods like Fast Fourier Transform (FFT) have limitations in efficiency.
  • Developing advanced algorithms is crucial for improved diagnostic capabilities.

Purpose of the Study:

  • To introduce and evaluate the Goertzel Algorithm (GA) for vocal signal processing in dysphonia.
  • To compare the efficiency and discriminatory power of GA against FFT.
  • To explore the potential of GA in enhancing dysphonia research and clinical applications.

Main Methods:

  • Vocal signals from healthy and dysphonia patients were processed using the Goertzel Algorithm (GA).
  • Performance metrics including processing time and memory usage were evaluated.
  • The discriminatory capability of GA in distinguishing between healthy and pathological vocal conditions was assessed.
  • Comparative analysis was conducted against the Fast Fourier Transform (FFT) method.

Main Results:

  • The Goertzel Algorithm (GA) demonstrated superior efficiency in processing time and reduced memory requirements compared to FFT.
  • GA exhibited enhanced discrimination between healthy and pathological vocal signals.
  • The algorithm's effectiveness in analyzing complex vocal characteristics was confirmed.

Conclusions:

  • The Goertzel Algorithm (GA) presents a viable and efficient alternative for vocal signal processing in dysphonia evaluation.
  • GA-based approaches can improve the reliability and speed of analysis, supporting clinical decision-making.
  • Further research into GA applications may significantly advance dysphonia diagnostics and patient monitoring.