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## transcribe ## transcribe
Simple script that uses OpenAI's Whisper to transcribe audio files from your local folders. Simple script that uses OpenAI's Whisper to transcribe audio files from your local folders.
## Note ## Note
This implementation and guide is mostly made for researchers not familiar with programming that want a way to transcribe their files locally, without internet connection, usually required within ethical data practices and frameworks. Two examples are shown, a normal workflow with internet connection. And one in which the model is loaded first, via openai-whisper, and then the transcription can be done without being connected to the internet. There is now also a GUI implementation, read below for more information. This implementation and guide is mostly made for researchers not familiar with programming that want a way to transcribe their files locally, without internet connection, usually required within ethical data practices and frameworks. Two examples are shown, a normal workflow with internet connection. And one in which the model is loaded first, via openai-whisper, and then the transcription can be done without being connected to the internet. There is now also a GUI implementation, read below for more information.
### Instructions ### Instructions
#### Requirements #### Requirements
1. This script was made and tested in an Anaconda environment with python 3.10. I recommend this method if you're not familiar with python.
1. This script was made and tested in an Anaconda environment with Python 3.10. I recommend this method if you're not familiar with Python.
See [here](https://docs.anaconda.com/anaconda/install/index.html) for instructions. You might need administrator rights. See [here](https://docs.anaconda.com/anaconda/install/index.html) for instructions. You might need administrator rights.
2. Whisper requires some additional libraries. The [setup](https://github.com/openai/whisper#setup) page states: "The codebase also depends on a few Python packages, most notably HuggingFace Transformers for their fast tokenizer implementation and ffmpeg-python for reading audio files." 2. Whisper requires some additional libraries. The [setup](https://github.com/openai/whisper#setup) page states: "The codebase also depends on a few Python packages, most notably HuggingFace Transformers for their fast tokenizer implementation and ffmpeg-python for reading audio files."
Users might not need to specifically install Transfomers. However, a conda installation might be needed for ffmepg[^1], which takes care of setting up PATH variables. From the anaconda prompt, type or copy the following: Users might not need to specifically install Transfomers. However, a conda installation might be needed for ffmpeg[^1], which takes care of setting up PATH variables. From the anaconda prompt, type or copy the following:
``` ```
conda install -c conda-forge ffmpeg-python conda install -c conda-forge ffmpeg-python
``` ```
3. The main functionality comes from openai-whisper. See their [page](https://github.com/openai/whisper) for details. As of 2023-03-22 you can install via: 3. The main functionality comes from openai-whisper. See their [page](https://github.com/openai/whisper) for details. As of 2023-03-22 you can install via:
``` ```
pip install -U openai-whisper pip install -U openai-whisper
``` ```
4. There is an option to run a batch file, which launches a GUI built on TKinter and TTKthemes. If using these options, make sure they are installed in your python build. You can install them via pip.
4. There is an option to run a batch file, which launches a GUI built on TKinter and TTKthemes. If using these options, make sure they are installed in your Python build. You can install them via pip.
``` ```
pip install tk pip install tk
``` ```
and and
``` ```
pip install ttkthemes pip install ttkthemes
``` ```
#### Using the script #### Using the script
This is a simple script with no installation. You can either clone the repository with This is a simple script with no installation. You can either clone the repository with
``` ```
git clone https://github.com/soderstromkr/transcribe.git git clone https://github.com/soderstromkr/transcribe.git
``` ```
and use the example.ipynb template to use the script.
**OR** download the ```transcribe.py``` file into your work folder. Then you can either import it to another script or notebook for use. I recommend jupyter notebook for new users, see the example below. (Remember to have transcribe.py and example.ipynb in the same working folder). and use the example.ipynb template to use the script,
#### Example with jupyter notebook **OR** download the ```transcribe.py``` file into your work folder. Then you can either import it to another script or notebook for use. I recommend [Jupyter Notebook](https://jupyter.org/) for new users, see the example below. (Remember to have `transcribe.py` and `example.ipynb` in the same working folder).
See [example](example.ipynb) for an implementation on jupyter notebook, also added an example for a simple [workaround](example_no_internet.ipynb) to transcribe while offline.
#### Using the GUI #### Example with Jupyter Notebook
See [example](example.ipynb) for an implementation on Jupyter Notebook, also added an example for a simple [workaround](example_no_internet.ipynb) to transcribe while offline.
#### Using the GUI
You can also run the GUI version from your terminal running ```python GUI.py``` or with the batch file called run_Windows.bat (for Windows user, Mac users should read the text file for instructions), just make sure to add your conda path to it. If you want to download a model first, and then go offline for transcription, I recommend running the model with the default sample folder, which will download the model locally. The GUI should look like this: You can also run the GUI version from your terminal running ```python GUI.py``` or with the batch file called run_Windows.bat (for Windows user, Mac users should read the text file for instructions), just make sure to add your conda path to it. If you want to download a model first, and then go offline for transcription, I recommend running the model with the default sample folder, which will download the model locally. The GUI should look like this:
![python GUI.py](gui_jpeg.jpg?raw=true) ![python GUI.py](gui_jpeg.jpg?raw=true)
[^1]: Advanced users can use ```pip install ffmpeg-python``` but be ready to deal with some [PATH issues](https://stackoverflow.com/questions/65836756/python-ffmpeg-wont-accept-path-why), which I encountered in Windows 11. [^1]: Advanced users can use ```pip install ffmpeg-python``` but be ready to deal with some [PATH issues](https://stackoverflow.com/questions/65836756/python-ffmpeg-wont-accept-path-why), which I encountered in Windows 11.
[![DOI](https://zenodo.org/badge/617404576.svg)](https://zenodo.org/badge/latestdoi/617404576) [![DOI](https://zenodo.org/badge/617404576.svg)](https://zenodo.org/badge/latestdoi/617404576)