Results 121 to 130 of about 261,201 (277)

Acoustic Measures Capture Speech Dysfunction in Spinocerebellar Ataxia

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Spinocerebellar ataxias (SCA) are hereditary cerebellar degenerative disorders with a common feature of dysarthria, involving impaired phonatory and articulatory control of speech, thereby affecting social communication. In this study, we investigated whether acoustic measures could objectively measure speech dysfunction and identify
Zena Fadel, Charlotte Hennessey, Hannah Lee, Pia Parekh, Sheng‐Han Kuo, Ami Kumar   +5 more
wiley   +1 more source

Characterization of Deep Learning-Based Speech-Enhancement Techniques in Online Audio Processing Applications. [PDF]

Sensors (Basel), 2023
Rascon C.
europepmc   +1 more source

Enhanced Feature Extraction Based on Absolute Sort Delta Mean Algorithm and MFCC for Noise Robustness Speech Recognition

, 2021
A. Nosan, Suchada Sitjongsataporn
openalex   +1 more source

Age‐Related Characteristics of SYT1‐Associated Neurodevelopmental Disorder

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives We describe the clinical manifestations and developmental abilities of individuals with SYT1‐associated neurodevelopmental disorder (Baker‐Gordon syndrome) from infancy to adulthood. We further describe the neuroradiological and electrophysiological characteristics of the condition at different ages, and explore the associations ...
Sam G. Norwitz, Josefine Eck, Joel S. Winston, Kate Baker   +3 more
wiley   +1 more source

A deep representation learning speech enhancement method using $β$-VAE [PDF]

, 2022
Yang Xiang, Jesper Lisby Højvang, Morten Højfeldt Rasmussen, Mads Græsbøll Christensen   +3 more
openalex   +1 more source

End‐to‐end speech‐denoising deep neural network based on residual‐attention gated linear units

Electronics Letters
In this letter, an improved gated linear unit (GLU) structure for end‐to‐end (E2E) speech enhancement is proposed. In the U‐Net structure, which is widely used as the foundational architecture for E2E deep neural network‐based speech denoising, the input
Seon Man Kim
doaj   +1 more source

Functional Connectivity Linked to Cognitive Recovery After Minor Stroke

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Patients with minor stroke exhibit slowed processing speed and generalized alterations in functional connectivity involving frontoparietal cortex (FPC). The pattern of connectivity evolves over time. In this study, we examine the relationship of functional connectivity patterns to cognitive performance, to determine ...
Vrishab Commuri, Isabella Dallasta, Ciaran Stone, Sophia Girgenti, Neda Gould, Rafael H. Llinas, Jonathan Z. Simon, Elisabeth Breese Marsh   +7 more
wiley   +1 more source

CGA-MGAN: Metric GAN Based on Convolution-Augmented Gated Attention for Speech Enhancement. [PDF]

Entropy (Basel), 2023
Chen H, Zhang X.
europepmc   +1 more source

Patch-based domain adversarial training for speech enhancement

Dianxin kexue
In deep learning-based speech enhancement methods, mismatched distributions between training data and test data are often encountered. These mismatches can include differences in speakers, speech content, noise types, and signal-to-noise ratios between ...
WANG Hongtao, LU Zhihua, YE Qingwei, ZHANG Lianjun   +3 more
doaj  

Effectiveness and Safety of Nusinersen and Risdiplam in Spinal Muscular Atrophy: A Systematic Review

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Spinal Muscular Atrophy (SMA) is a rare genetic disorder marked by progressive muscle weakness and mobility loss. It has a profound physical, emotional and social impact on patients and caregivers, requiring comprehensive medical and supportive care.
Amin Mehrabian, Peter Auguste, Amy Grove, Anna Brown, Janette Parr, Mubarak Patel, Furqan Butt, Jeremiah Donoghue, Mehdi Yousefi, Jo Parsons   +9 more
wiley   +1 more source