Acoustic Representation

Acoustic representation focuses on transforming raw audio signals into meaningful numerical representations that capture relevant information for various speech and audio processing tasks. Current research emphasizes developing robust and efficient representations using deep learning models, such as transformers and generative adversarial networks (GANs), often incorporating multi-scale and multi-modal approaches to leverage both acoustic and linguistic features. These advancements are driving improvements in applications ranging from speech recognition and synthesis to speaker identification and emotion analysis, ultimately leading to more accurate and versatile audio technologies.