CLARITY: Addressing Bias in Text-to-Speech Generation with Contextual Adaptation
Analysis
This research from ArXiv explores mitigating biases in text-to-speech generation. The study introduces CLARITY, a novel approach to tackle dual-bias by adapting language models and retrieving accents based on context.
Key Takeaways
Reference / Citation
View Original"CLARITY likely uses techniques to modify or refine the output of text-to-speech models, potentially addressing issues of fairness and representation."