A novel hybrid model integrating MFCC and acoustic parameters for voice disorder detection

V Verma, A Benjwal, A Chhabra, SK Singh, S Kumar… - Scientific Reports, 2023 - nature.com
Voice is an essential component of human communication, serving as a fundamental
medium for expressing thoughts, emotions, and ideas. Disruptions in vocal fold vibratory …

Voice pathology detection using machine learning technique

FT AL-Dhief, NMA Latiff, NNNA Malik… - 2020 IEEE 5th …, 2020 - ieeexplore.ieee.org
Recent proposed researches have witnessed that voice pathology detection systems can
effectively contribute to the voice disorders assessment and provide early detection of voice …

[PDF][PDF] Deep learning solution for pathological voice detection using LSTM-based autoencoder hybrid with multi-task learning

KG Dávid Sztahó, TM Gábriel - I14th International Joint …, 2021 - researchgate.net
In this paper, a deep learning approach is introduced to detect pathological voice disorders
from continuous speech. Speech as bio-signal is getting more and more attention as a …

Dysphonia detection based on voice signals using naive bayes classifier

FT Al-Dhief, NMA Latiff, NNNA Malik… - 2022 IEEE 6th …, 2022 - ieeexplore.ieee.org
Voice pathology detection has gained a lot of attention in the last few decades. Furthermore,
this field is considered an active topic in the healthcare area. However, most machine …

Predictions for three-month postoperative vocal recovery after thyroid surgery from spectrograms with deep neural network

JH Lee, CY Lee, JS Eom, M Pak, HS Jeong, HY Son - Sensors, 2022 - mdpi.com
Despite the lack of findings in laryngeal endoscopy, it is common for patients to undergo
vocal problems after thyroid surgery. This study aimed to predict the recovery of the patient's …

Spasmodic dysphonia detection using machine learning classifiers

E Hadjaidji, MCA Korba, K Khelil - … International Conference on …, 2021 - ieeexplore.ieee.org
Spasmodic Dysphonia (SD) is a neurological problem that involves the laryngeal muscles to
malfunction. It is characterized by inappropriate contraction of the laryngeal muscles during …

Using ASR posterior probability and acoustic features for voice disorder classification

MG Tulics, G Szaszák, K Mészáros… - 2020 11th IEEE …, 2020 - ieeexplore.ieee.org
Dysphonia can be caused not only by the frequent use voice, but many other reasons,
including environmental noise, environmental pollution and dry environment. Dysphonia …

Aspects of methodology for interaction analysis

C Vogel, M Koutsombogera… - 2020 11th IEEE …, 2020 - ieeexplore.ieee.org
Observational methods in interaction analysis are defended. Observational methods are
distinguished from experimental methods with respect to the mode of data collection. Other …

[PDF][PDF] Cross-lingual detection of dysphonic speech for Dutch and Hungarian datasets

D Sztahó, MG Tulics, J Qi, K Vicsi - Proceedings of the 15th …, 2022 - lirias.kuleuven.be
Dysphonic voices can be detected using features derived from speech samples. Works
aiming at this topic usually deal with mono-lingual experiments using a speech dataset in a …

[PDF][PDF] Application for Detecting Depression, Parkinson's Disease and Dysphonic Speech.

G Kiss, D Sztahó, MG Tulics - Interspeech, 2021 - isca-archive.org
Abstract In this Show&Tell presentation we demonstrate an application that is able to assess
a voice sample according to three different voice disorders: depression, Parkinson's disease …