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Non-linear prediction for oesophageal voice analysis.
L Landini1, C Manfredi, V Positano
1Department of Information Engineering, University of Pisa, Via Diotisalvi 2, 56126 Pisa, Italy.
Medical Engineering & Physics
|September 19, 2002
Summary
Non-linear prediction methods reveal distinct oesophageal voice patterns. Normal voices exhibit stable deterministic behavior, while pathological voices show reduced non-linear dynamics and instability.
Area of Science:
- Speech Science
- Bioacoustics
- Non-linear Dynamics
Background:
- Oesophageal voice is an alternative speech method for individuals with laryngeal impairments.
- Understanding the acoustic characteristics of oesophageal voice is crucial for improving speech production and intelligibility.
- Non-linear dynamics offer advanced tools for analyzing complex biological signals like voice.
Purpose of the Study:
- To apply non-linear prediction methods to oesophageal voice analysis.
- To differentiate between normal and pathological oesophageal voice behavior.
- To enhance the understanding of the underlying dynamics of oesophageal voice production.
Main Methods:
- Analysis of oesophageal voice signals from normal and pathological subjects.
- Reconstruction of phase space for voice signals.
- Application of non-linear prediction techniques, including local linear approximation and the S-Map method.
Main Results:
- Normal oesophageal voice signals demonstrate a non-linear, stable, and deterministic behavior.
- Pathological oesophageal voice signals exhibit a reduction in non-linear contributions.
- Time series analysis indicates increased instability in pathological oesophageal voice patterns.
Conclusions:
- Non-linear prediction methods are effective in characterizing oesophageal voice dynamics.
- Distinct non-linear patterns differentiate normal and pathological oesophageal voices.
- Findings suggest potential for improved diagnosis and therapy through non-linear voice analysis.