Perspectives on Generative Sound Design: A Generative Soundscapes Showcase

Recent advancements in generative neural networks, particularly transformer-based models, have introduced novel possibilities for sound design. This study explores the use of generative pre-trained transformers (GPT) to create complex, multilayered soundscapes from textual and visual prompts. A custom pipeline is proposed, featuring modules for converting the source input into structured sound descriptions and subsequently generating cohesive auditory outputs. As a complementary solution, a granular synthesizer prototype was developed to enhance the usability of generative audio samples by enabling their recombination into seamless and non-repetitive soundscapes. The integration of GPT models with granular synthesis demonstrates significant potential for innovative audio production, paving the way for advancements in professional sound-design workflows and immersive audio applications.