Name
Title | ||
|---|---|---|
A Two-Dimensional Framework of Multiple Kernel Subspace Learning for Recognizing Emotion in Speech. |
Abstract | ||
|---|---|---|
As a highly active topic in computational paralinguistics, speech emotion recognition (SER) aims to explore ideal representations for emotional factors in speech. In order to improve the performance of SER, multiple kernel learning (MKL) dimensionality reduction has been utilized to obtain effective information for recognizing emotions. However, the solution of MKL usually provides only one nonneg... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TASLP.2017.2694704 | IEEE/ACM Transactions on Audio, Speech, and Language Processing |
Keywords | Field | DocType |
Kernel,Speech,Training,Speech processing,Speech recognition,Optimization,Emotion recognition | Speech processing,Dimensionality reduction,Computer science,Tree kernel,Artificial intelligence,Kernel (linear algebra),Embedding,Subspace topology,Pattern recognition,Multiple kernel learning,Kernel Fisher discriminant analysis,Speech recognition,Machine learning | Journal |
Volume | Issue | ISSN |
25 | 7 | 2329-9290 |
Citations | PageRank | References |
3 | 0.41 | 39 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xinzhou Xu | 1 | 38 | 3.45 |
| Jun Deng | 2 | 278 | 18.59 |
| Nicholas Cummins | 3 | 349 | 32.93 |
| Zixing Zhang | 4 | 397 | 31.73 |
| Chen Wu | 5 | 7 | 1.13 |
| Li Zhao | 6 | 198 | 22.70 |
| Björn Schuller | 7 | 6749 | 463.50 |