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Voice Quality

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Convolutional neural network-based automatic classification of midsagittal tongue gestural targets using B-mode ultrasound images.

The Journal of the Acoustical Society of America
Tongue gestural target classification is of great interest to researchers in the speech production field. Recently, deep convolutional neural networks (CNN) have shown superiority to standard feature extraction techniques in a variety of domains. In ...

Auditory feature representation using convolutional restricted Boltzmann machine and Teager energy operator for speech recognition.

The Journal of the Acoustical Society of America
In this letter, authors propose an auditory feature representation technique with the filterbank learned using an annealing dropout convolutional restricted Boltzmann machine (ConvRBM) and noise-robust energy estimation using the Teager energy operat...

A transfer learning approach to goodness of pronunciation based automatic mispronunciation detection.

The Journal of the Acoustical Society of America
Goodness of pronunciation (GOP) is the most widely used method for automatic mispronunciation detection. In this paper, a transfer learning approach to GOP based mispronunciation detection when applying maximum F1-score criterion (MFC) training to de...

Demographic and Symptomatic Features of Voice Disorders and Their Potential Application in Classification Using Machine Learning Algorithms.

Folia phoniatrica et logopaedica : official organ of the International Association of Logopedics and Phoniatrics (IALP)
BACKGROUND: Studies have used questionnaires of dysphonic symptoms to screen voice disorders. This study investigated whether the differential presentation of demographic and symptomatic features can be applied to computerized classification.

Detection of Pathological Voice Using Cepstrum Vectors: A Deep Learning Approach.

Journal of voice : official journal of the Voice Foundation
OBJECTIVES: Computerized detection of voice disorders has attracted considerable academic and clinical interest in the hope of providing an effective screening method for voice diseases before endoscopic confirmation. This study proposes a deep-learn...

A Survey on Machine Learning Approaches for Automatic Detection of Voice Disorders.

Journal of voice : official journal of the Voice Foundation
The human voice production system is an intricate biological device capable of modulating pitch and loudness. Inherent internal and/or external factors often damage the vocal folds and result in some change of voice. The consequences are reflected in...

Discrimination of "hot potato voice" caused by upper airway obstruction utilizing a support vector machine.

The Laryngoscope
OBJECTIVES/HYPOTHESIS: "Hot potato voice" (HPV) is a thick, muffled voice caused by pharyngeal or laryngeal diseases characterized by severe upper airway obstruction, including acute epiglottitis and peritonsillitis. To develop a method for determini...

Machine learning based identification of relevant parameters for functional voice disorders derived from endoscopic high-speed recordings.

Scientific reports
In voice research and clinical assessment, many objective parameters are in use. However, there is no commonly used set of parameters that reflect certain voice disorders, such as functional dysphonia (FD); i.e. disorders with no visible anatomical c...

Deep Learning for Voice Gender Identification: Proof-of-concept for Gender-Affirming Voice Care.

The Laryngoscope
OBJECTIVES/HYPOTHESIS: The need for gender-affirming voice care has been increasing in the transgender population in the last decade. Currently, objective treatment outcome measurements are lacking to assess the success of these interventions. This s...

Machine Learning-based Voice Assessment for the Detection of Positive and Recovered COVID-19 Patients.

Journal of voice : official journal of the Voice Foundation
Many virological tests have been implemented during the Coronavirus Disease 2019 (COVID-19) pandemic for diagnostic purposes, but they appear unsuitable for screening purposes. Furthermore, current screening strategies are not accurate enough to effe...