The Neuralacoustics Project: Exploring Deep-Learnin for Lightweight Numerical Modeling Synthesis
Other conference contribution, 2022

Workshop, Session 1.

We present a newly started project called Neuralacoustics, aimed at using embedded AI to reduce the computational requirements of numerical modeling synthesis. To achieve this goal, we propose a novel design pipeline, in which neural networks are first trained off-line to approximate the behavior of target interactive acoustic systems, and then deployed on embedded and mobile platforms as real-time synthesis engines.

musical acoustics

deep learning

non-linear acoustics

machine learning

Author

Victor Zappi

Northeastern University

Kivanc Tatar

Chalmers, Computer Science and Engineering (Chalmers), Data Science and AI

Embedded AI for NIME: Challenges and Opportunities Workshop at New Interfaces for Musical Expression

The International Conference on New Interfaces for Musical Expression
Auckland, New Zealand,

Areas of Advance

Information and Communication Technology

Subject Categories

Embedded Systems

More information

Latest update

7/2/2024 7