Update README.md

README.md

@@ -113,6 +113,10 @@ We evaluated the speculative decoding setup for Whisper-large-v3-singlish on the
 | SASRBench-v1   | 38.00%                   | 42.00%                    |
 | AMI            | 38.00%                   | 43.00%                    |
 
+### Conclusion
+
+While it does not outperform Large-Turbo in WER, the Draft-enhanced Large model demonstrates strong speculative acceptance rates (~38–43%), indicating meaningful potential for runtime gains through early prediction acceptance. In latency-sensitive applications, it offers a compelling middle ground between the high accuracy of Large-Turbo and the slower inference of standard decoding.
+
 ## Disclaimer
 
 While this model has been fine-tuned to better recognize Singlish, users may experience inaccuracies, biases, or unexpected outputs, particularly in challenging audio conditions or with speakers using non-standard variations. Use of this model is at your own risk; the developers and distributors are not liable for any consequences arising from its use. Please validate results before deploying in any sensitive or production environment.