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speech-classification

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In this notebook, we aim to recognize speech commands using classification. For this purpose, we used the SPEECHCOMMANDS dataset and the deep convolutional model M5. The code is written in Python and designed for the PyTorch platform.

  • Updated Jun 18, 2024
  • Jupyter Notebook

A convolutional neural network for gender classification, which achieved an F1-score of 94.3% when tested on the RAVDESS dataset. Created as postgraduate coursework, the report is included. The report also discusses Sodiq Adebiy's CNN, which I'd recommend looking at to anyone interested in emotion classification.

  • Updated Jun 22, 2022
  • Jupyter Notebook

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