Accuracy Analysis of the Multiparametric Acoustic Voice Indices, the VWI, AVQI, ABI, and DSI Measures, in Differentiating between Normal and Dysphonic Voices.

The study aimed to investigate and compare the accuracy and robustness of the multiparametric acoustic voice indices (MAVIs), namely the Dysphonia Severity Index (DSI), Acoustic Voice Quality Index (AVQI), Acoustic Breathiness Index (ABI), and Voice Wellness Index (VWI) measures in differentiating normal and dysphonic voices. The study group consisted of 129 adult individuals including 49 with normal voices and 80 patients with pathological voices. The diagnostic accuracy of the investigated MAVI in differentiating between normal and pathological voices was assessed using receiver operating characteristics (ROC).

Smartphone-Based Voice Wellness Index Application for Dysphonia Screening and Assessment: Development and Reliability.

Objective: This study aimed to develop a Voice Wellness Index (VWI) application combining the acoustic voice quality index (AVQI) and glottal function index (GFI) data and to evaluate its reliability in quantitative voice assessment and normal versus pathological voice differentiation.

Study Design: Cross-sectional study.

Methods: A total of 135 adult participants (86 patients with voice disorders and 49 patients with normal voices) were included in this study.

Pareto-Optimized Non-Negative Matrix Factorization Approach to the Cleaning of Alaryngeal Speech Signals.

The problem of cleaning impaired speech is crucial for various applications such as speech recognition, telecommunication, and assistive technologies. In this paper, we propose a novel approach that combines Pareto-optimized deep learning with non-negative matrix factorization (NMF) to effectively reduce noise in impaired speech signals while preserving the quality of the desired speech. Our method begins by calculating the spectrogram of a noisy voice clip and extracting frequency statistics.

Reliability of Universal-Platform-Based Application in AVQI Measurements Captured with Different Smartphones.

The aim of the study was to develop a universal-platform-based (UPB) application suitable for different smartphones for estimation of the Acoustic Voice Quality Index (AVQI) and evaluate its reliability in AVQI measurements and normal and pathological voice differentiation. Our study group consisted of 135 adult individuals, including 49 with normal voices and 86 patients with pathological voices. The developed UPB "" application installed on five iOS and Android smartphones was used for AVQI estimation.

An iOS-based VoiceScreen application: feasibility for use in clinical settings-a pilot study.

Objectives: To elaborate the application suitable for smartphones for estimation of Acoustic Voice Quality Index (AVQI) and evaluate its usability in the clinical setting.

Methods: An elaborated AVQI automatization and background noise monitoring functions were implemented into a mobile "VoiceScreen" application running the iOS operating system. A study group consisted of 103 adult individuals with normal voices (n = 30) and 73 patients with pathological voices.

Lightweight Deep Learning Model for Assessment of Substitution Voicing and Speech after Laryngeal Carcinoma Surgery.

Laryngeal carcinoma is the most common malignant tumor of the upper respiratory tract. Total laryngectomy provides complete and permanent detachment of the upper and lower airways that causes the loss of voice, leading to a patient's inability to verbally communicate in the postoperative period. This paper aims to exploit modern areas of deep learning research to objectively classify, extract and measure the substitution voicing after laryngeal oncosurgery from the audio signal.

Accuracy of Acoustic Voice Quality Index Captured With a Smartphone - Measurements With Added Ambient Noise.

Objective: To evaluate the accuracy of Acoustic Voice Quality Index (AVQI) measures obtained from voice recordings simultaneously using oral and smartphone microphones in a sound-proof room, and to compare them with AVQIs obtained from the same smartphone voice recordings with added ambient noise.

Methods: A study group of 183 subjects with normal voices (n = 86) and various voice disorders (n = 97) was asked to read aloud a standard text and sustain the vowel /a/. The controlled ambient noise averaged at 29.

Exploring the feasibility of the combination of acoustic voice quality index and glottal function index for voice pathology screening.

Purpose: The aim of this study was to explore the diagnostic value of the combination of Acoustic Voice Quality Index (AVQI) and Glottal Function Index (GFI) as a screening tool for voice disorders, and to compare the AVQI measurements obtained using oral and smartphone (SP) microphones.

Methods: A study group consisted of 183 adult individuals including 86 subjects with normal voice and 97 patients with pathological voice. Voice recordings were performed simultaneously with an oral AKG Perception 220 and SP iPhone 6s microphones.

Diagnostic Accuracy of Dysphonia Classification of DSI and AVQI.

Objective: The Dysphonia Severity Index (DSI) and the Acoustic Voice Quality Index (AVQI) have been successfully investigated to quantify voice quality. The aim of the present study was to evaluate the diagnostic accuracy of both measurements in comparison with the dysphonia classification.

Methods: In total, 264 subjects with vocally healthy voices (n = 105) and with various voice disorders (n = 159) were included in the study.

A comparison of Dysphonia Severity Index and Acoustic Voice Quality Index measures in differentiating normal and dysphonic voices.

Purpose: The aim of the study was to investigate and compare the feasibility and robustness of the Acoustic Voice Quality Index (AVQI) and the Dysphonia Severity Index (DSI) in diagnostic accuracy, differentiating normal and dysphonic voices.

Methods: A group of 264 subjects with normal voices (n = 105) and with various voice disorders (n = 159) were asked to read aloud a text and to sustain the vowel /a/. Both speech tasks were concatenated, and perceptually rated for dysphonia severity by five voice clinicians.

The Influence of Gender and Age on the Acoustic Voice Quality Index and Dysphonia Severity Index: A Normative Study.

Objectives: The Acoustic Voice Quality Index (AVQI) and the Dysphonia Severity Index (DSI) are commonly used in research and clinical practice to quantify voice quality. The aim of this study was to investigate the influence of gender and age on AVQI and again on DSI.

Methods: In total, 123 vocally healthy adults (68 females, 55 males, and age ranging between 20 and 79 years) were evaluated.