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speech-to-text

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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
magnetron.artificial-intelligence-2.0.mincloud.proxia--INSTINCTIVE-MIND-5

✭ MAGNETRON ™ ✭: This is a Google Colab/Jupyter Notebook for developing a HEARING PROXIA (B) when working with ARTIFICIAL INTELLIGENCE 2.0 ™ (ARTIFICIAL INTELLIGENCE 2.0™ is part of MAGNETRON ™ TECHNOLOGY).

  • Updated Sep 22, 2022
  • Jupyter Notebook

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