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Voice

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Toward an Automatic Quality Assessment of Voice-Based Telemedicine Consultations: A Deep Learning Approach.

Sensors (Basel, Switzerland)
Maintaining a high quality of conversation between doctors and patients is essential in telehealth services, where efficient and competent communication is important to promote patient health. Assessing the quality of medical conversations is often h...

Artificial Intelligence Can Improve Patient Management at the Time of a Pandemic: The Role of Voice Technology.

Journal of medical Internet research
Artificial intelligence-driven voice technology deployed on mobile phones and smart speakers has the potential to improve patient management and organizational workflow. Voice chatbots have been already implemented in health care-leveraging innovativ...

A Comparison of an Artificial Intelligence Tool to Fundamental Frequency as an Outcome Measure in People Seeking a More Feminine Voice.

The Laryngoscope
OBJECTIVES/HYPOTHESIS: An artificial intelligence (AI) tool was developed using audio clips of cis-male and cis-female voices based on spectral analysis to assess %probability of a voice being perceived as female (%Prob♀). This program was validated ...

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...

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 ...

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...

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...

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...

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...