Sound Design
Sound design encompasses the creation, manipulation, and application of sound for various purposes, aiming to achieve specific aesthetic, communicative, or functional goals. Current research focuses on developing novel methods for sound generation, manipulation, and analysis, employing techniques like deep learning architectures (e.g., variational autoencoders, transformers), and exploring cross-modal interactions between sound and other modalities such as vision and language. These advancements are improving applications ranging from assistive technologies for the visually impaired to enhancing the realism and interactivity of virtual and augmented reality experiences, as well as advancing fields like medical transcription and machinery fault detection.
Papers
AI (r)evolution -- where are we heading? Thoughts about the future of music and sound technologies in the era of deep learning
Giovanni Bindi, Nils Demerlé, Rodrigo Diaz, David Genova, Aliénor Golvet, Ben Hayes, Jiawen Huang, Lele Liu, Vincent Martos, Sarah Nabi, Teresa Pelinski, Lenny Renault, Saurjya Sarkar, Pedro Sarmento, Cyrus Vahidi, Lewis Wolstanholme, Yixiao Zhang, Axel Roebel, Nick Bryan-Kinns, Jean-Louis Giavitto, Mathieu Barthet
Dense 2D-3D Indoor Prediction with Sound via Aligned Cross-Modal Distillation
Heeseung Yun, Joonil Na, Gunhee Kim
Sound Design Strategies for Latent Audio Space Explorations Using Deep Learning Architectures
Kıvanç Tatar, Kelsey Cotton, Daniel Bisig
Music Representing Corpus Virtual: An Open Sourced Library for Explorative Music Generation, Sound Design, and Instrument Creation with Artificial Intelligence and Machine Learning
Christopher Johann Clarke
AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head
Rongjie Huang, Mingze Li, Dongchao Yang, Jiatong Shi, Xuankai Chang, Zhenhui Ye, Yuning Wu, Zhiqing Hong, Jiawei Huang, Jinglin Liu, Yi Ren, Zhou Zhao, Shinji Watanabe
Adaptive Representations of Sound for Automatic Insect Recognition
Marius Faiß, Dan Stowell