AIMC Topic: Voice

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Scenario-Based Programming of Voice-Controlled Medical Robotic Systems.

Sensors (Basel, Switzerland)
An important issue in medical robotics is communication between physicians and robots. Speech-based communication is of particular advantage in robot-assisted surgery. It frees the surgeon's hands; hence, he can focus on the principal tasks. Man-mach...

Diagnosis of Early Glottic Cancer Using Laryngeal Image and Voice Based on Ensemble Learning of Convolutional Neural Network Classifiers.

Journal of voice : official journal of the Voice Foundation
OBJECTIVES: The purpose of study is to improve the classification accuracy by comparing the results obtained by applying decision tree ensemble learning, which is one of the methods to increase the classification accuracy for a relatively small datas...

Automated detection of mild cognitive impairment and dementia from voice recordings: A natural language processing approach.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Automated computational assessment of neuropsychological tests would enable widespread, cost-effective screening for dementia.

Exploring Longitudinal Cough, Breath, and Voice Data for COVID-19 Progression Prediction via Sequential Deep Learning: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: Recent work has shown the potential of using audio data (eg, cough, breathing, and voice) in the screening for COVID-19. However, these approaches only focus on one-off detection and detect the infection, given the current audio sample, b...

Design of Proactive Interaction for In-Vehicle Robots Based on Transparency.

Sensors (Basel, Switzerland)
Based on the transparency theory, this study investigates the appropriate amount of transparency information expressed by the in-vehicle robot under two channels of voice and visual in a proactive interaction scenario. The experiments are to test and...

Neurogenerative Disease Diagnosis in Cepstral Domain Using MFCC with Deep Learning.

Computational and mathematical methods in medicine
Because underlying cognitive and neuromuscular activities regulate speech signals, biomarkers in the human voice can provide insight into neurological illnesses. Multiple motor and nonmotor aspects of neurologic voice disorders arise from an underlyi...

Decoding lip language using triboelectric sensors with deep learning.

Nature communications
Lip language is an effective method of voice-off communication in daily life for people with vocal cord lesions and laryngeal and lingual injuries without occupying the hands. Collection and interpretation of lip language is challenging. Here, we pro...

The shallow of your smile: the ethics of expressive vocal deep-fakes.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
Rapid technological advances in artificial intelligence are creating opportunities for real-time algorithmic modulations of a person's facial and vocal expressions, or 'deep-fakes'. These developments raise unprecedented societal and ethical question...

Identifying individuals with recent COVID-19 through voice classification using deep learning.

Scientific reports
Recently deep learning has attained a breakthrough in model accuracy for the classification of images due mainly to convolutional neural networks. In the present study, we attempted to investigate the presence of subclinical voice feature alteration ...

Negative content in auditory verbal hallucinations: a natural language processing approach.

Cognitive neuropsychiatry
INTRODUCTION: Negative content of auditory verbal hallucinations (AVH) is a strong predictor of distress and impairment. This paper quantifies emotional voice-content in order to explore both subjective (i.e. perceived) and objectively (i.e. linguist...