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AI Testing

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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:

Have a working emotion recognition system developed in Python.

Understand how to use and test open-source AI models for voice recognition.

Be equipped with the knowledge to create and manage automated testing pipelines on GitHub.

Gain insights into the challenges of AI model testing and how to overcome them.

What you’ll need

Experience in automation testing

Basic familiarity with programming concepts (Python knowledge is helpful but not required)

Access to a computer with Python installed and the ability to install additional software as needed.

Workshop details

Track 4

14:00h - 18:00h · May 28th

4 hour workshop

AI Testing

General Level

Workshop in English


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.