How to Detect and Display Unique Speakers

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.

Quick Setup

• 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.txt to install project dependencies
• Add your AssemblyAI API key to the configure.py file
• Run the application using the streamlit run app.py

How it Works

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.

Main Dependencies

• Streamlit The fastest way to build data apps in Python
• Pandas Powerful data structures for data analysis, time series, and statistics

Contact Us

If you have any questions, please feel free to reach out to our Support team - [email protected]!