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Extracting speech spectrogram of speech signal based on generalized S-transform.
PLoS One
January 2025
College of Computer Science and Technology, Xinjiang University, Urumqi, Xinjiang, China.
In speech signal processing, time-frequency analysis is commonly employed to extract the spectrogram of speech signals. While many algorithms exist to achieve this with high-quality results, they often lack the flexibility to adjust the resolution of the extracted spectrograms. However, applications such as speech recognition and speech separation frequently require spectrograms of varying resolutions.
View Article and Find Full Text PDFClinical Decision Support Using Speech Signal Analysis: Systematic Scoping Review of Neurological Disorders.
J Med Internet Res
January 2025
Knight Foundation of Computing & Information Sciences, Florida International University, Miami, FL, United States.
Background: Digital biomarkers are increasingly used in clinical decision support for various health conditions. Speech features as digital biomarkers can offer insights into underlying physiological processes due to the complexity of speech production. This process involves respiration, phonation, articulation, and resonance, all of which rely on specific motor systems for the preparation and execution of speech.
View Article and Find Full Text PDFAnalysis and Categorization of Various Types of Vocal Distortion in Rock, Metal, Pop Styles, and Throat Singing Observed by High-Speed Digital Imaging.
J Voice
January 2025
Faculty of Design, Kyushu University, 4-9-1 Shiobaru, Minami-ku, Fukuoka 815-8540, Japan.
Introduction: Vocal distortion, also known as a scream or growl, is used worldwide as an essential technique in singing, especially in rock and metal, and as an ethnic voice in Mongolian singing. However, the production mechanism of vocal distortion is not yet clearly understood owing to limited research on the behavior of the larynx, which is the source of the distorted voice.
Objectives: This study used high-speed digital imaging (HSDI) to observe the larynx of professional singers with exceptional singing skills and determine the laryngeal dynamics in the voice production of various vocal distortions.
Alzheimer's disease recognition based on waveform and spectral speech signal processing.
Biomed Eng Lett
January 2025
School of Medical Devices, Shanghai University of Medicine & Health Sciences, Shanghai, 201318 China.
Alzheimer's disease (AD) is a neurodegenerative disorder with an irreversible progression. Currently, it is diagnosed using invasive and costly methods, such as cerebrospinal fluid analysis, neuroimaging, and neuropsychological assessments. Recent studies indicate that certain changes in language ability can predict early cognitive decline, highlighting the potential of speech analysis in AD recognition.
View Article and Find Full Text PDFClassification of arteriovenous fistula sounds using a convolutional block attention module and long short-term memory neural network.
Front Physiol
December 2024
Department of Nephrology, People's Hospital of Zhengzhou University, Zhengzhou, China.
The assessment of vascular accessibility in patients undergoing hemodialysis is predominantly reliant on manual inspection, a method that is associated with several limitations. In this study, we propose an alternative approach by recording the acoustic signals produced by the arteriovenous fistula (AVF) and employing deep learning techniques to analyze these sounds as an objective complement to traditional AVF evaluation methods. Auscultation sounds were collected from 800 patients, with each recording lasting between 24 and 30 s.
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