Deep Learning as Feature Encoding for Emotion Recognition
Deep learning is popular as an end-to-end framework extracting the prominent features and performing the classification also. In this paper, we extensively investigate deep networks as an alternate to feature encoding technique of low level descriptors for emotion recognition on the benchmark EmoDB dataset. Fusion performance with such obtained encoded features with other available features is also investigated. Highest performance to date in the literature is observed.
PDF Abstract
Datasets
Add Datasets
introduced or used in this paper
Results from the Paper
Submit
results from this paper
to get state-of-the-art GitHub badges and help the
community compare results to other papers.
Methods
No methods listed for this paper. Add
relevant methods here
