AIMC Topic: Speech Acoustics
Clear Filters Showing 31 to 40 of 46 articles
Detection of Neurogenic Voice Disorders Using the Fisher Vector Representation of Cepstral Features.
Journal of voice : official journal of the Voice Foundation
May 1, 2025
Neurogenic voice disorders (NVDs) are caused by damage or malfunction of the central or peripheral nervous system that controls vocal fold movement. In this paper, we investigate the potential of the Fisher vector (FV) encoding in automatic detection...
Dysphonia
Voice Disorders
Speech Production Measurement
Phonation
Voice Quality
Speech Acoustics
Vocal Cord Paralysis
Vocal Cords
Reproducibility of Results
Aged
Young Adult
Adult
Male
Middle Aged
Predictive Value of Tests
Case-Control Studies
Humans
Signal Processing, Computer-Assisted
Support Vector Machine
Databases, Factual
Acoustics
Female
Sound Spectrography
A WaveNet-based model for predicting the electroglottographic signal from the acoustic voice signal.
The Journal of the Acoustical Society of America
Apr 1, 2025
The electroglottographic (EGG) signal offers a non-invasive approach to analyze phonation. It is known, if not obvious, that the onset of vocal fold contacting has a substantial effect on how the vocal folds vibrate and on the quality of the voice. G...
The machine learning-based prediction of the sound pressure level from pathological and healthy speech signals.
The Journal of the Acoustical Society of America
Mar 1, 2025
Vocal intensity is quantified by sound pressure level (SPL). The SPL can be measured by either using a sound level meter or by comparing the energy of the recorded speech signal with the energy of the recorded calibration tone of a known SPL. Neither...
Developing a smart system for binary classification of disordered voices using machine learning.
American journal of otolaryngology
Jan 1, 2025
OBJECTIVES: Voice disorder is characterized by disruptions in voice quality caused by issues in vocal fold vibration during phonation. The study explored the application of machine learning, based on the Random Forest (RF) and Decision Tree (DT) mode...
Using articulatory feature detectors in progressive networks for multilingual low-resource phone recognitiona).
The Journal of the Acoustical Society of America
Nov 1, 2024
Systems inspired by progressive neural networks, transferring information from end-to-end articulatory feature detectors to similarly structured phone recognizers, are described. These networks, connecting the corresponding recurrent layers of pre-tr...
Evaluating the consistency of lenition measures: Neural networks' posterior probability, intensity velocity, and duration.
The Journal of the Acoustical Society of America
Aug 1, 2024
Predictions of gradient degree of lenition of voiceless and voiced stops in a corpus of Argentine Spanish are evaluated using three acoustic measures (minimum and maximum intensity velocity and duration) and two recurrent neural network (Phonet) meas...
Research on Tone Enhancement of Mandarin Pitch Controllable Electrolaryngeal Speech Based on Deep Learning.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
The deep learning-based electrolaryngeal (EL) voice conversion methods have achieved good results in non-tonal languages. However, the effectiveness in tonal languages, such as Mandarin Chinese (Mandarin), remains suboptimal. The reason may be that t...
ADT Network: A Novel Nonlinear Method for Decoding Speech Envelopes From EEG Signals.
Trends in hearing
Jan 1, 2024
Decoding speech envelopes from electroencephalogram (EEG) signals holds potential as a research tool for objectively assessing auditory processing, which could contribute to future developments in hearing loss diagnosis. However, current methods stru...
[Current methods of acoustic analysis of voice: a review].
Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery
Dec 1, 2022
Acoustic analysis of the voice, as an objective, quantitative, non-invasive and reproducible method for the evaluation of voice quality, can be used to detect and analyze the acoustic characteristics of normal, artistic or pathological voice. With th...
Use of a Deep Recurrent Neural Network to Reduce Wind Noise: Effects on Judged Speech Intelligibility and Sound Quality.
Trends in hearing
Jan 1, 2018
Despite great advances in hearing-aid technology, users still experience problems with noise in windy environments. The potential benefits of using a deep recurrent neural network (RNN) for reducing wind noise were assessed. The RNN was trained using...
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