High-Value Synthetic Supervision for Parameter-Efficient Adaptation of a Compact Japanese Speech Model
A compact Japanese audio model learned an end-to-end speech-to-structure mapping by adapting it using a few hundred synthetic examples. This demonstrates that small models can acquire specific, narrow capabilities from high-quality synthetic supervision, proving capability acquisition rather than just device performance.