Matías Zañartu

This paper uses machine learning models to create fast surrogates for biomechanical laryngeal control models, enabling real-time applications with reduced computational costs.

This study uses an asymmetric vocal fold model to explore how muscle imbalance affects vocal fold vibration, showing significant asymmetry in paralysis and minor asymmetry in dysphonia.

This study examines acoustic and electroencephalography changes during the Lombard effect in participants with normal hearing and voice, finding increased vocal intensity and altered ERP responses.

The paper introduces the Chirp Analyzer (CA) for estimating EFR amplitude and latency, showing it outperforms traditional methods in accuracy and robustness to noise.

This study examines how averaging methods affect auditory steady-state response (ASSR) amplitudes in rats, finding that independent epochs yield higher amplitudes and better detection rates.