Voice problems among Slovenian physicians compared to the teachers: Prevalence and risk factors
Background: Physicians are classified as nonvocal professionals. However, they do have a certain vocal load during one-to-one communications with patients.
Maja Šereh Bahar +2 more
doaj
Examining Therapy Duration in Adults With Voice Disorders. [PDF]
Fujiki RB, Thibeault SL.
europepmc +1 more source
This work presents a deep learning model to autonomously recognize and classify the secretion retention into three levels for patients receiving invasive mechanical ventilation, achieving 89.08% accuracy. This model can be implemented to ventilators by edge computing, whose feasibility is approved.
Shuai Wang +6 more
wiley +1 more source
Review of Memristors for In‐Memory Computing and Spiking Neural Networks
Memristors uniquely enable energy‐efficient, brain‐inspired computing by acting as both memory and synaptic elements. This review highlights their physical mechanisms, integration in crossbar arrays, and role in spiking neural networks. Key challenges, including variability, relaxation, and stochastic switching, are discussed, alongside emerging ...
Mostafa Shooshtari +2 more
wiley +1 more source
Awareness of Vocal Hygiene Education among Government Secondary School Teachers
Background: The impact of voice disorders in professionals have a negative effect on the quality of life of those who suffer from them. Voice problems negatively affects their job performance.
Humaira Shamim Kiyani +1 more
doaj
Measuring Perceived Voice Disorders and Quality of Life among Female University Teaching Faculty. [PDF]
Al Awaji NN +7 more
europepmc +1 more source
Differentiation between depression and bipolar disorder in child and adolescents by voice features [PDF]
Jie Luo +8 more
openalex +1 more source
Functional Speech and Voice Disorders: Case Series and Literature Review [PDF]
David S. Chung +3 more
openalex +1 more source
Robust Dysarthric Speech Recognition with GAN Enhancement and LLM Correction
This study tackles dysarthric speech recognition by combining generative adversarial network (GAN)‐generated synthetic data with large language model (LLM)‐based error correction. The approach integrates three key elements: an improved CycleGAN to generate synthetic dysarthric speech for data augmentation, a multimodal automatic speech recognition core
Yibo He +3 more
wiley +1 more source
Vocal tasks for acoustic and/or auditory perceptual analysis for discriminating individuals with and without voice disorders: a systematic review protocol. [PDF]
Gunjawate DR +3 more
europepmc +1 more source

