Name
Title | ||
|---|---|---|
Attention-based convolutional neural network and long short-term memory for short-term detection of mood disorders based on elicited speech responses. |
Abstract | ||
|---|---|---|
•Short-term detection of mood disorder based on elicited speech responses.•Attention-based CNN outputs the emotion profile of each speech response.•Long-Short Term Memory characterizes the temporal evolution of the emotion profile.•Attention-based LSTM focuses on the pertinent responses of the entire response. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.patcog.2018.12.016 | Pattern Recognition |
Keywords | Field | DocType |
Mood disorder detection,Convolutional neural network,Long short-term memory,Attention model | Mood,Bipolar disorder,Mood disorders,Pattern recognition,Convolutional neural network,Domain adaptation,Long short term memory,Attention model,Speech recognition,Artificial intelligence,Mental health,Mathematics | Journal |
Volume | Issue | ISSN |
88 | 1 | 0031-3203 |
Citations | PageRank | References |
2 | 0.41 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kun-Yi Huang | 1 | 14 | 5.00 |
| Chung-Hsien Wu | 2 | 1099 | 116.79 |
| Ming-Hsiang Su | 3 | 21 | 6.83 |