Name
Title | ||
|---|---|---|
Speaker-Independent Silent Speech Recognition From Flesh-Point Articulatory Movements Using an LSTM Neural Network. |
Abstract | ||
|---|---|---|
Silent speech recognition (SSR) converts nonaudio information such as articulatory movements into text. SSR has the potential to enable persons with laryngectomy to communicate through natural spoken expression. Current SSR systems have largely relied on speaker-dependent recognition models. The high degree of variability in articulatory patterns across different speakers has been a barrier for de... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TASLP.2017.2758999 | IEEE/ACM Transactions on Audio, Speech, and Language Processing |
Keywords | Field | DocType |
Biology,Speech recognition,Memory,Training data,Physiology,Maximum likelihood linear regression,Recurrent neural networks,Recurrent neural networks | Training set,Normalization (statistics),Pattern recognition,Computer science,Recurrent neural network,Speech recognition,Maximum likelihood linear regression,Artificial intelligence,Artificial neural network | Journal |
Volume | Issue | ISSN |
25 | 12 | 2329-9290 |
Citations | PageRank | References |
4 | 0.43 | 29 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Myung Jong Kim | 1 | 31 | 6.30 |
| Beiming Cao | 2 | 8 | 1.51 |
| ted mau | 3 | 11 | 2.29 |
| Jun Wang | 4 | 144 | 15.26 |