AI Testing
HALF-DAY WORKSHOP
Emotion Recognition in Voice: Building and Testing AI Models with Open Source Tools
Dive into the fascinating world of AI as we embark on a journey to develop an emotion recognition system from scratch using Python and open-source models like Llama and Mistral. This hands-on workshop is designed to guide participants through the intricacies of building and testing language models, culminating in the creation of a fully automated testing pipeline.
- Introduction to emotion recognition in voice and its applications.
- Setting up the development environment using Python and your favorite text editor.
- Overview of open-source models (Llama, Mistral) for emotion recognition.
- Step-by-step guide to developing an emotion recognition system in Python.
- Best practices for testing language models, including unit and integration testing.
- Creating automated testing pipelines with GitHub for continuous integration.
- Discussion on the challenges of testing language models and leveraging AI for testing purposes.
What you’ll learn
From this workshop you will learn how to:
What you’ll need
Workshop details
Enrique Sánchez-Bayuela
Enrique is an Engineering and QA Manager for over 13 years, leading dynamic teams at companies like Aircall and Cabify. Currently, he specializes in AI testing using ChatGPT, innovating in simulating production traffic and evaluating audio transcriptions. Enrique also shares knowledge as a university professor. What he cherishes about testing is the challenge of ensuring product excellence and the continuous evolution in methodologies, especially with the advent of AI. Being an active contributor to the Spanish QA community, Enrique’s shared insights at various conferences.