Amir Hossein Poorjam — accepted AI-conference papers

2019

Quality Control of Voice Recordings in Remote Parkinson's Disease Monitoring Using the Infinite Hidden Markov Model

Amir Hossein Poorjam, Yordan P. Raykov, Reham Badawy, Jesper Rindom Jensen, Mads Græsbøll Christensen, Max A. Little

ICASSP 2019accepted

The performance of voice-based systems for remote monitoring of Parkinson's disease is highly dependent on the degree of adherence of the recordings to the test protocols, which probe for specific symptoms. Identifying segments of the signal that adhere to the protocol assumptions is typically perfo…

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2018

A Parametric Approach for Classification of Distortions in Pathological Voices

Amir Hossein Poorjam, Max A. Little, Jesper Rindom Jensen, Mads Græsbøll Christensen

ICASSP 2018accepted

In biomedical acoustics, distortion in voice signals, commonly present during acquisition and transmission, adversely affects acoustic features extracted from pathological voice. Information on the type of distortion can help in compensating for its effects. This paper proposes a new approach to det…

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2018

A Supervised Approach to Global Signal-to-Noise Ratio Estimation for Whispered and Pathological Voices

Amir Hossein Poorjam, Max A. Little, Jesper Rindom Jensen, Mads Græsbøll Christensen

ICASSP 2018accepted

The presence of background noise in signals adversely affects the performance of many speech-based algorithms. Accurate estimation of signal-to-noise-ratio (SNR), as a measure of noise level in a signal, can help in compensating for noise effects. Most existing SNR estimation methods have been devel…

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