This is an example of how you can use AssemblyAI's Speaker Labels model to automatically detect unique speakers and display a turn-by-turn dialogue of the conversation.
- Download project files by running
git clone https://github.com/AssemblyAI/speaker-diarization.git - Navigate to the project folder
- Create a new virtual environment
- Activate the new virtual environment and run
pip install -r requirements.txtto install project dependencies - Add your AssemblyAI API key to the
configure.pyfile - Run the application using the
streamlit run app.py
The file you upload is submitted to AssemblyAI for transcription with speaker_labels set to true. When the transcript is complete you will receive a JSON response that contains a top-level key names utterances. Data from the utterance key is iterated upon to Streamlit is used display a turn-by-turn transcript of "who spoke when" in the browser.
- Streamlit The fastest way to build data apps in Python
- Pandas Powerful data structures for data analysis, time series, and statistics
If you have any questions, please feel free to reach out to our Support team - support@assemblyai.com!