Use case : Synthetic data generation for machine learning
The Treble SDK is a powerful tool designed to simplify the creation of high-quality acoustic training data. It enables the simulation of realistic acoustic scenes, incorporating complex materials, geometries, furnishings, directional sound sources, and microphone arrays. By leveraging these capabilities, developers can enhance audio machine learning (ML) algorithms for tasks such as speech enhancement, source localization, blind room estimation, echo cancellation, room adaptation, and generative AI audio. Independent research has validated the benefits of wave-based synthetic acoustic data, demonstrating its ability to significantly improve ML performance. See independent research here
In this tutorial we show how to setup a batch simulation in treble using geometries from our geometry database.