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 …
Synchronization of fuzzy-chaotic systems with Z-controller in secure communication
KM Babanli, RO Kabaoglu - Information Sciences, 2024 - Elsevier
Soft Computing approaches may be effectively used for the aim to improve security of
communication systems. Recently, we proposed a technique for fuzzy-chaotic masking …
communication systems. Recently, we proposed a technique for fuzzy-chaotic masking …
[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 …
Exploiting hidden representations from a DNN-based speech recogniser for speech intelligibility prediction in hearing-impaired listeners
An accurate objective speech intelligibility prediction algorithms is of great interest for many
applications such as speech enhancement for hearing aids. Most algorithms measures the …
applications such as speech enhancement for hearing aids. Most algorithms measures the …
Ideal ratio mask estimation based on cochleagram for audio-visual monaural speech enhancement
S Balasubramanian, R Rajavel, A Kar - Applied Acoustics, 2023 - Elsevier
In this paper, the estimation of the ideal ratio mask (IRM) has been carried out based on
speech cochleagram and visual cues using Audio-Visual Multichannel Convolutional Neural …
speech cochleagram and visual cues using Audio-Visual Multichannel Convolutional Neural …
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 …
Estimation of ideal binary mask for audio-visual monaural speech enhancement
S Balasubramanian, R Rajavel, A Kar - Circuits, Systems, and Signal …, 2023 - Springer
The estimation of the Ideal Binary Mask (IBM) based on speech cochleagram and visual
cues were carried out in this paper to improve the speech intelligibility and quality using an …
cues were carried out in this paper to improve the speech intelligibility and quality using an …
[HTML][HTML] Comparison of ideal mask-based speech enhancement algorithms for speech mixed with white noise at low mixture signal-to-noise ratios
The literature shows that the intelligibility of noisy speech can be improved by applying an
ideal binary or soft gain mask in the time-frequency domain for signal-to-noise ratios (SNRs) …
ideal binary or soft gain mask in the time-frequency domain for signal-to-noise ratios (SNRs) …
Robust Features with Convolutional Autoencoder Speech Command Recognition
Today, deep learning (DL) has proven to be a prominent method in many recognition tasks.
However, deep learning-based Automatic Speech Recognition (ASR) has degraded …
However, deep learning-based Automatic Speech Recognition (ASR) has degraded …
Machine Learning Application to Study Human Brain: The Investigation of Brain Microstructure and Speech Decoding Based on Cortical Neural Activity
J Chen - 2024 - search.proquest.com
Abstract Machine learning and deep neural networks have succeeded in various computer
vision tasks involving modalities ranging from natural to medical images. The advancement …
vision tasks involving modalities ranging from natural to medical images. The advancement …