Automatic Detection of Articulatory-Based Disfluencies in Primary Progressive Aphasia [0.03%]
原发性进行性失语症的口吃基于发音自动检测
Jiachen Lian,Xuanru Zhou,Chenxu Guo et al.
Jiachen Lian et al.
Speech corpora are collections of textual data derived from human verbal output and speech signals that can be processed from a variety of perspectives, including formal or semantic content, to serve analyses of different levels of linguist...
Speech Acoustic Markers Can Detect Mild Cognitive Impairment in Parkinson's Disease [0.03%]
语音声学标志可以检测帕金森病的轻度认知障碍
Kara M Smith,James R Williamson,Thomas F Quatieri
Kara M Smith
Background: Speech biomarkers have been used to assess motor dysfunction in people with Parkinson's disease (PD), but speech biomarkers for mild cognitive impairment in PD (PD-MCI) have not been well studied. ...
Time Scale Network: An Efficient Shallow Neural Network For Time Series Data in Biomedical Applications [0.03%]
时间尺度网络：一种用于生物医学应用的时间序列数据高效浅层神经网络
Trevor Meyer,Camden Shultz,Najim Dehak et al.
Trevor Meyer et al.
Time series data is often composed of information at multiple time scales, particularly in biomedical data. While numerous deep learning strategies exist to capture this information, many make networks larger, require more data, are more de...
Modeling Social Distancing and Quantifying Epidemic Disease Exposure in a Built Environment [0.03%]
基于建筑环境的社交疏离模拟及疾病暴露量化的研究
Chaitra Hegde,Ali Bahrami Rad,Reza Sameni et al.
Chaitra Hegde et al.
As we transition away from pandemic-induced isolation and social distancing, there is a need to estimate the risk of exposure in built environments. We propose a novel metric to quantify social distancing and the potential risk of exposure ...
Detection of SARS-CoV-2 in COVID-19 Patient Nasal Swab Samples Using Signal Processing [0.03%]
基于信号处理的新型冠状病毒肺炎患者鼻咽拭子样品检测方法研究
Mahmoud Al Ahmad,Lillian J A Olule,Mohammed Meetani et al.
Mahmoud Al Ahmad et al.
This work presents an opto-electrical method that measures the viral nucleocapsid protein and anti-N antibody interactions to differentiate between SARS-CoV-2 negative and positive nasal swab samples. Upon light exposure of the patient nasa...
Project Achoo: A Practical Model and Application for COVID-19 Detection From Recordings of Breath, Voice, and Cough [0.03%]
Project Achoo：一种针对新冠肺炎的呼吸、声音和咳嗽录音的实用检测模型与应用
Alexander Ponomarchuk,Ilya Burenko,Elian Malkin et al.
Alexander Ponomarchuk et al.
The COVID-19 pandemic created significant interest and demand for infection detection and monitoring solutions. In this paper, we propose a machine learning method to quickly detect COVID-19 using audio recordings made on consumer devices. ...
Application of Tensor Decomposition to Gene Expression of Infection of Mouse Hepatitis Virus Can Identify Critical Human Genes and Efffective Drugs for SARS-CoV-2 Infection [0.03%]
张量分解在小鼠肝炎病毒基因表达中的应用可识别SARS-CoV-2感染的关键人类基因和有效药物
Y-H Taguchi,Turki Turki
Y-H Taguchi
To better understand the genes with altered expression caused by infection with the novel coronavirus strain SARS-CoV-2 causing COVID-19 infectious disease, a tensor decomposition (TD)-based unsupervised feature extraction (FE) approach was...
Improved subglottal pressure estimation from neck-surface vibration in healthy speakers producing non-modal phonation [0.03%]
健康人发声时亚声门压的估计方法改进
Jon Z Lin,Víctor M Espinoza,Katherine L Marks et al.
Jon Z Lin et al.
Subglottal air pressure plays a major role in voice production and is a primary factor in controlling voice onset, offset, sound pressure level, glottal airflow, vocal fold collision pressures, and variations in fundamental frequency. Previ...
A Review of Automated Speech and Language Features for Assessment of Cognitive and Thought Disorders [0.03%]
基于言语和语言特征的神经认知及精神疾病的自动化评估技术研究进展
Rohit Voleti,Julie M Liss,Visar Berisha
Rohit Voleti
It is widely accepted that information derived from analyzing speech (the acoustic signal) and language production (words and sentences) serves as a useful window into the health of an individual's cognitive ability. In fact, most neuropsyc...
Dense Recurrent Neural Networks for Accelerated MRI: History-Cognizant Unrolling of Optimization Algorithms [0.03%]
基于历史信息的优化算法解卷积加速MRI中的密集循环神经网络
Seyed Amir Hossein Hosseini,Burhaneddin Yaman,Steen Moeller et al.
Seyed Amir Hossein Hosseini et al.
Inverse problems for accelerated MRI typically incorporate domain-specific knowledge about the forward encoding operator in a regularized reconstruction framework. Recently physics-driven deep learning (DL) methods have been proposed to use...