AIMC Topic: Speech

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Linear versus deep learning methods for noisy speech separation for EEG-informed attention decoding.

Journal of neural engineering
OBJECTIVE: A hearing aid's noise reduction algorithm cannot infer to which speaker the user intends to listen to. Auditory attention decoding (AAD) algorithms allow to infer this information from neural signals, which leads to the concept of neuro-st...

Evaluation of Hyperparameter Optimization in Machine and Deep Learning Methods for Decoding Imagined Speech EEG.

Sensors (Basel, Switzerland)
Classification of electroencephalography (EEG) signals corresponding to imagined speech production is important for the development of a direct-speech brain-computer interface (DS-BCI). Deep learning (DL) has been utilized with great success across s...

Characterizing soundscapes across diverse ecosystems using a universal acoustic feature set.

Proceedings of the National Academy of Sciences of the United States of America
Natural habitats are being impacted by human pressures at an alarming rate. Monitoring these ecosystem-level changes often requires labor-intensive surveys that are unable to detect rapid or unanticipated environmental changes. Here we have developed...

Brain-optimized extraction of complex sound features that drive continuous auditory perception.

PLoS computational biology
Understanding how the human brain processes auditory input remains a challenge. Traditionally, a distinction between lower- and higher-level sound features is made, but their definition depends on a specific theoretical framework and might not match ...

Speech Quality Feature Analysis for Classification of Depression and Dementia Patients.

Sensors (Basel, Switzerland)
Loss of cognitive ability is commonly associated with dementia, a broad category of progressive brain diseases. However, major depressive disorder may also cause temporary deterioration of one's cognition known as pseudodementia. Differentiating a tr...

Deep learning-based smart speaker to confirm surgical sites for cataract surgeries: A pilot study.

PloS one
Wrong-site surgeries can occur due to the absence of an appropriate surgical time-out. However, during a time-out, surgical participants are unable to review the patient's charts due to their aseptic hands. To improve the conditions in surgical time-...

Machine translation of cortical activity to text with an encoder-decoder framework.

Nature neuroscience
A decade after speech was first decoded from human brain signals, accuracy and speed remain far below that of natural speech. Here we show how to decode the electrocorticogram with high accuracy and at natural-speech rates. Taking a cue from recent a...

Identification of Speech Characteristics to Distinguish Human Personality of Introversive and Extroversive Male Groups.

International journal of environmental research and public health
According to the similarity-attraction theory, humans respond more positively to people who are similar in personality. This observation also holds true between humans and robots, as shown by recent studies that examined human-robot interactions. Thu...

On the localness modeling for the self-attention based end-to-end speech synthesis.

Neural networks : the official journal of the International Neural Network Society
Attention based end-to-end speech synthesis achieves better performance in both prosody and quality compared to the conventional "front-end"-"back-end" structure. But training such end-to-end framework is usually time-consuming because of the use of ...

LFP-Net: A deep learning framework to recognize human behavioral activities using brain STN-LFP signals.

Journal of neuroscience methods
BACKGROUND: Recognition of human behavioral activities using local field potential (LFP) signals recorded from the Subthalamic Nuclei (STN) has applications in developing the next generation of deep brain stimulation (DBS) systems. DBS therapy is oft...