https://github.com/dataprofessor/transcriber-v2
https://github.com/dataprofessor/transcriber-v2
Last synced: about 1 year ago
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- Host: GitHub
- URL: https://github.com/dataprofessor/transcriber-v2
- Owner: dataprofessor
- Created: 2023-05-13T03:40:58.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2023-05-13T16:14:31.000Z (about 3 years ago)
- Last Synced: 2024-11-11T12:23:23.614Z (over 1 year ago)
- Language: Python
- Size: 65.4 KB
- Stars: 4
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# transcriber-app
# Watch the tutorial video
[How to build your own Speech-to-Text Transcription App in Python using AssemblyAI](https://youtu.be/Kj0JtjAxxKA)
# 1. Obtain the AssemblyAI API key
Obtain your free [AssemblyAI API key](https://www.assemblyai.com/?utm_source=youtube&utm_medium=social&utm_campaign=dataprofessor).
# 2. Running transcriber as command line tool
Firstly, copy and paste the AssemblyAI API key into the `api.txt` file (you can replace the text `replace_with_your_AssemblyAI_API_key` with your own API key).
Secondly, install prerequisite `pytube` library by typing the following:
```
pip3 install pytube
```
Thirdly, run the transcriber by typing the following (note that you can replace the URL with a YouTube video of your choice):
```
python3 transcriber.py -i "https://youtu.be/mkVjrB8g6mM"
```
# 3. Running transcriber as a Streamlit app
To recreate this web app on your own computer, do the following.
### Create conda environment (Optional)
Firstly, we will create a conda environment called *transcriber*
```
conda create -n transcriber python=3.7.9
```
Secondly, we will login to the *transcriber* environment
```
conda activate transcriber
```
### Download GitHub repo
```
git clone https://github.com/dataprofessor/transcriber-app
```
### Pip install libraries
```
pip install -r requirements.txt
```
### Launch the app
```
streamlit run app.py
```