Hi everybody,
Given the different methods of speech feature extraction (IS09, IS10,...), which one do you suggest for EMODB and IEMOCAP datasets?
Fatemeh Daneshfar
Hope this will help
Cepstral features are popular in the speech processing (speech and speaker recognition) and the most widely used is MFCC
Article On the Speech Properties and Feature Extraction Methods in S...
Kashif Ameer
Thank you very much for your reply and the mentioned paper. How about interspeech features (IS09, IS10,...)? Is there any idea?
Fatemeh Daneshfar
features sets from. 2009 (IS09-Emotion) [11], 2010 (IS10-Paraling)
hope this will help
https://d-nb.info/1218972203/34
The key to speech emotion recognition is the feature extraction process. The quality of the features directly influences the accuracy of classification results. If you are interested in typically feature extraction, the Mel-frequency Cepstrum coefficient (MFCC) is the most used representation of the spectral property of voice signals as well as you can try energy, pitch, formant frequency, Linear Prediction Cepstrum Coefficients (LPCC), and modulation spectral features (MSFs).
According to your suggested IS09 and IS10 which one is better so both are working good and there is no big difference but I recommend trying high-level (DL) features, it will be defiantly better than low-level.
Mustaqeem Khan
Thank you very much for your reply. Do you mean an end-to-end system, by the high-level features?
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