https://github.com/anyantudre/audio-transformers-hugging-face

Explore the application of transformers to audio data in this course. Learn to tackle tasks like speech recognition, audio classification, and text-to-speech generation using cutting-edge transformer models.
https://github.com/anyantudre/audio-transformers-hugging-face

audio-classification audio-processing automatic huggingface speech-recognition speech-synthesis speech-to-text

Last synced: 12 days ago
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Explore the application of transformers to audio data in this course. Learn to tackle tasks like speech recognition, audio classification, and text-to-speech generation using cutting-edge transformer models.

• Host: GitHub
• URL: https://github.com/anyantudre/audio-transformers-hugging-face
• Owner: ANYANTUDRE
• Created: 2024-10-05T09:31:18.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-11-02T21:40:22.000Z (4 months ago)
• Last Synced: 2024-12-17T01:17:55.319Z (2 months ago)
• Topics: audio-classification, audio-processing, automatic, huggingface, speech-recognition, speech-synthesis, speech-to-text
• Language: Jupyter Notebook
• Homepage:
• Size: 7.12 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        


  
 Audio Transformers Course (key takeaways) - Hugging Face 🤗

  


    🕸 LinkedIn • 

    📙 Kaggle • 

    💻 Medium Blog • 

    🤗 Hugging Face • 

  






This repository contains an summarized version or, rather let's say, my **key takeaways** from the [**Hugging Face Audio course**](https://huggingface.co/learn/audio-course). 

The aim is to have a few **notes from the course and the code snippets** that seem most important to keep handy in each section. **Think of it as a sort of "cheat sheet" to quickly explore the most important concepts.** If you've already taken the original or similar course, or have some basic knowledge of Audio Transformers, you'll undoubtly find this useful as a quick refresher on the various concepts.

### Original course:

- **License:** The original course is released under the permissive [Apache 2 license](https://www.apache.org/licenses/LICENSE-2.0.html).

- **Citation:**

```@misc{huggingfacecourse,

  author = {Hugging Face},

  title = {The Hugging Face Course, 2022},

  howpublished = "\url{https://huggingface.co/course}",

  year = {2022},

  note = "[Online; accessed ]"

}

```