aryaaftab / light-sernet

Light-SERNet: A lightweight fully convolutional neural network for speech emotion recognition

Arya Aftab 👋

As a Data Scientist and Machine Learning Engineer, I worked independently and as a team member for several projects, including voice command, speech emotion recognition, speech enhancement, etc. My desire to learn more about Machine Learning, Deep Learning, their applications and deploy them into real-world models.

Hello, My name is Arya!

• 🔭 I’m currently working on Meta-learning and Self-supervised Learning
• 📋 Previously worked on Speech Recognition, Speech Emotion Recognition, and Tiny Machine Learning
• 🎓 Master of Electrical Engineering (Communication Systems), Sharif University of Technology
• 🎓 Bachelor of Biomedical Engineering (Bioelectric), Amirkabir University of Technology

GitHub Stats

light-sernet's Issues

Test data seen during training - correct results?

Hi,

I just noticed in your code that you are using the test data from the CV fold as validation data and save the best model based on the validation accuracy. This is sort of cherry picking the model. Do you by any chance have updated results where you do not use the test set during training?

Thanks,
Adriana

I trained in Colab and get models, but how do I test these models ?

InvalidArgumentError: Cannot batch tensors with different shapes in component 0.

Hello! Good job! But I have an error. I want to test the model with my audio files. I have created a folder my_test_3.0s_Segmented in date where the audio is tagged by emotion. Everything goes well, but I always get an error at the moment: list(test_dataset.as_numpy_iterator())
InvalidArgumentError: Cannot batch tensors with different shapes in component 0. First element had shape [103,40,1] and element 1 had shape [92,40,1]. [Op:IteratorGetNext]
This prevents me from testing. I used my code on test data generated while training the model. The code works and I get the result. How can I fix it?

cannot run the IEMOCAP dataset on windows

Hello, could you show the data folder architecture so I understand the way you organised the dataset.
I kept getting errors to segment the data.
I extracted the IEMOCAP_full_release in the data folder the renamed it as IEMOCAP, however, I kept getting errors of files not found.

About the license for this model

Thank you for sharing your great code. smiley_cat

What is the license for this model? I'd like to cite it to the repository I'm working on if possible, but I want to post the license correctly.

https://github.com/PINTO0309/PINTO_model_zoo/tree/main/382_Light-SERNet

Thank you.

code_error

data_read_error

I solved this problem,tensorflow-gpu version is too high

MFCC hop size problem.

"Good job on the paper. However, there seems to be a discrepancy regarding the frame overlaps and hop size between your text and the provided code. In your paper, it's stated that a Hamming window is used to split the audio signal into 64-ms frames with 16-ms overlaps, which are considered as quasi-stationary segments. From this, it would logically follow that the hop size is 48 ms.

However, in the hyperparameters.py file, it's stated "FRAME_STEP = 256". Given a sampling rate (fs) of 16 kHz, this implies a hop size of 16 ms, not 48 ms. Could you please clarify if there's a typographical error in the paper, or if there's a specific reason for this inconsistency?"

function cleaning_directory_filename()

I think the function cleaning_directory_filename() breaks the speaker independence in the paper, i.e., 10-fold cross-validation, causing speaker overlap in the training and test sets. Removing this function, I get an 8% drop in WA. Could you explain my confusion.