Contribution
Enhancing Programming Skills in Audio Signal Analysis and AI: A Problem-Based Learning Approach
* Presenting author
Abstract:
The challenge of teaching AI programming in media engineering and informatics lies not only in imparting technical knowledge but also in cultivating essential future skills such as problem-solving, creativity, and collaboration. In AI Media Programming courses, students are introduced to the intersection of audio signal analysis, AI, musical acoustics, and generative music systems through a problem-based learning approach. This method encourages students to think critically and apply deep learning knowledge to real-world scenarios.Rather than focusing solely on theory, students learn project based, by programming neural networks that control parameters in digital audio workstations through gestures and facial expressions, or by exploring generative music creation and evaluating AI-driven creative systems. Thus, students expand their understanding of both technical and creative applications of AI.The success of these projects—ranging from gesture-based chord generation to emotion based music generation—illustrates the importance of integrating AI with media tools. Beyond technical expertise, students develop the ability to solve complex problems, work in teams, and apply their creativity to cutting-edge applications. By engaging students in these challenges, educators prepare them for a rapidly evolving industry where handling and evaluating AI plays a crucial role in shaping media experiences.