Privacy-Preserving Adaptation of ASR for Low-Resource Domains

This ArXiv paper addresses a critical challenge in Automatic Speech Recognition (ASR): adapting models to low-resource environments while preserving privacy. The research likely focuses on techniques to improve ASR performance in under-resourced languages or specialized domains without compromising user data.

• •Addresses the problem of adapting ASR models to low-resource settings.
• •Emphasizes privacy-preserving techniques, crucial in sensitive applications.
• •Potentially introduces novel methods to improve ASR accuracy in resource-constrained environments.