Name
Title | ||
|---|---|---|
OVERT SPEECH RETRIEVAL FROM NEUROMAGNETIC SIGNALS USING WAVELETS AND ARTIFICIAL NEURAL NETWORKS |
Abstract | ||
|---|---|---|
Speech production involves the synchronization of neural activity between the speech centers of the brain and the oral-motor system, allowing for the conversion of thoughts into meaningful sounds. This hierarchical mechanism is hindered due to partial or complete paralysis of the articulators for patients suffering from locked-in-syndrome. These patients are in dire need of effective brain-communication interfaces (BCIs), which can at least provide a level of communication assistance. In this study, we tried to decode overt (loud) speech directly from the brain via non-invasive magnetoen-cephalography (MEG) signals to build the foundation for a faster, direct brain to text mapping BCI. A shallow Artificial Neural Network (ANN) was trained with wavelet features of the MEG signals for this objective. Experimental results show that a direct speech decoding is possible from MEG signals. Moreover, we found that the jaw motion and MEG signals may have complimentary information for speech decoding. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/GlobalSIP.2018.8646401 | 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP) |
Keywords | Field | DocType |
Magnetoencephalography,wavelet,speech production,artificial neural network | Synchronization,Computer science,Direct speech,Brain–computer interface,Speech recognition,Decoding methods,Artificial neural network,Speech production,Magnetoencephalography,Wavelet | Conference |
ISSN | ISBN | Citations |
2376-4066 | 978-1-7281-1295-4 | 1 |
PageRank | References | Authors |
0.37 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Debadatta Dash | 1 | 2 | 1.42 |
| Paul Ferrari | 2 | 2 | 2.44 |
| Saleem Malik | 3 | 2 | 0.75 |
| Jun Wang | 4 | 144 | 15.26 |