Accuracy problem about speech-emotion-analyzer

[nikhil2593]

same..not getting specified accuracy with the provided model architecture and dataset.

[MiteshPuthran]

Hello @torrentillo, this is the exact code that I had used to train my model. In order to achieve higher accuracy, there are 3 things that come to my mind.

1. Try playing with the parameters while building the model and test it out.
2. Extract more features from the audio files. This can be done by increasing the sampling rate.
3. Add more data by copying the existing files. (Not the best way, but can improve the accuracy)

Hope this helps.

[torrentillo]

Hi Mites,

I used the exact code and I can't get the accuracy you got, what about the dataset you used? could you please update the dataset you used to this post??

[MiteshPuthran]

I had used the dataset from the links I posted in the README file.

[torrentillo]

Yes, but when you filter only by 5 emotions you have like 1300 audios for training instead of 900 that I have if I do the same, so you've trained your model with some extra data that is not in the like you posted in the README file.

Thank you

[beachboysqq]

Hi,I am trying using different models and increase the dropout value.But it seems still overfit. I can get a hign acc on training but low acc on test. Plz give me some suggestions~ many thanks~

[torrentillo]

Hi beach,

I've achieved a 70 % accuracy with this model :

Ridge = sklearn.linear_model.Ridge()