Document paper and latest validation results

README.md

@@ -19,6 +19,7 @@ This repository is the default model source for the [`DeepFilterNetCoreML`](http
 ## Origin
 
 - Original project: [Rikorose/DeepFilterNet](https://github.com/Rikorose/DeepFilterNet)
+- Paper: [DeepFilterNet: Perceptually Motivated Real-Time Speech Enhancement](https://arxiv.org/abs/2305.08227)
 - Swift runtime and conversion: [kylehowells/DeepFilterNet-mlx](https://github.com/kylehowells/DeepFilterNet-mlx)
 - Conversion script: [`Scripts/Conversion/convert_deepfilternet_to_coreml.py`](https://github.com/kylehowells/DeepFilterNet-mlx/blob/feature/deepfilternet4/Scripts/Conversion/convert_deepfilternet_to_coreml.py)
 
@@ -36,7 +37,7 @@ The fixed 30 ms delay is separate from model execution time and application audi
 
 ## Validation
 
-The validated Swift streaming path measured 0.999993 correlation to the official PyTorch CLI output. On the development Apple Silicon Mac, steady per-hop Core ML compute was approximately 0.288 ms and the 52.13-second validation clip processed in 1.548 seconds. Performance varies by device and OS.
+The validated Swift streaming path measured 0.999993 correlation to the official PyTorch CLI output. A fresh end-to-end run from the original stereo source, including Swift downmix/resampling, measured 0.999969 correlation and 42.13 dB signal-to-error ratio. On the development Apple Silicon Mac, unpaced steady per-hop Core ML compute was 0.264 ms and the 52.13-second validation clip processed in 1.494 seconds (34.9x real time). Performance and paced callback latency vary by device, operating system, and concurrent load.
 
 ## Swift usage