A neural speech decoding framework leveraging deep learning and speech synthesis
Decoding human speech from neural signals is essential for brain–computer interface (BCI)
technologies that aim to restore speech in populations with neurological deficits. However, it …
technologies that aim to restore speech in populations with neurological deficits. However, it …
Single-neuronal elements of speech production in humans
Humans are capable of generating extraordinarily diverse articulatory movement
combinations to produce meaningful speech. This ability to orchestrate specific phonetic …
combinations to produce meaningful speech. This ability to orchestrate specific phonetic …
Dataset of speech production in intracranial electroencephalography
Speech production is an intricate process involving a large number of muscles and cognitive
processes. The neural processes underlying speech production are not completely …
processes. The neural processes underlying speech production are not completely …
Innovative Deep Learning Methods for Precancerous Lesion Detection
With the continuous advancement of socio-economic levels and relentless innovation in
modern medical technologies, there's been a significant increase in the importance people …
modern medical technologies, there's been a significant increase in the importance people …
[PDF][PDF] Advancements in AI for Oncology: Developing an Enhanced YOLOv5-based Cancer Cell Detection System
As artificial intelligence (AI) theory becomes more sophisticated and its utilization spreads
across daily life, education, and professional settings, the adoption of AI for medical …
across daily life, education, and professional settings, the adoption of AI for medical …
TokenUnify: Scalable Autoregressive Visual Pre-training with Mixture Token Prediction
Autoregressive next-token prediction is a standard pretraining method for large-scale
language models, but its application to vision tasks is hindered by the non-sequential nature …
language models, but its application to vision tasks is hindered by the non-sequential nature …
[HTML][HTML] Subject-Agnostic Transformer-Based Neural Speech Decoding from Surface and Depth Electrode Signals
Objective: This study investigates speech decoding from neural signals captured by
intracranial electrodes. Most prior works can only work with electrodes on a 2D grid (ie …
intracranial electrodes. Most prior works can only work with electrodes on a 2D grid (ie …
[HTML][HTML] Large-scale Foundation Models and Generative AI for BigData Neuroscience
Recent advances in machine learning have led to revolutionary breakthroughs in computer
games, image and natural language understanding, and scientific discovery. Foundation …
games, image and natural language understanding, and scientific discovery. Foundation …
Time Series Modeling for Heart Rate Prediction: From ARIMA to Transformers
H Ni, S Meng, X Geng, P Li, Z Li, X Chen… - arXiv preprint arXiv …, 2024 - arxiv.org
Cardiovascular disease (CVD) is a leading cause of death globally, necessitating precise
forecasting models for monitoring vital signs like heart rate, blood pressure, and ECG …
forecasting models for monitoring vital signs like heart rate, blood pressure, and ECG …
The brain nebula: minimally invasive brain–computer interface by endovascular neural recording and stimulation
Q He, Y Yang, P Ge, S Li, X Chai, Z Luo… - Journal of …, 2024 - jnis.bmj.com
A brain–computer interface (BCI) serves as a direct communication channel between brain
activity and external devices, typically a computer or robotic limb. Advances in technology …
activity and external devices, typically a computer or robotic limb. Advances in technology …