---
license: apache-2.0
tags:
- ENOT-AutoDL
- SpeechEnhancement
---

# MP-SENet optimization on VoiceBank+DEMAND dataset with ENOT-AutoDL.

This repository contains the optimized version of [MP-SENet](https://github.com/yxlu-0102/MP-SENet) model.
Number of multiplication and addition operations (MACs) was used for computational complexity measurement. PESQ score was used as a quality metric.

## Optimization results  

We use MACs as a latency measure because this metric is device-agnostic and implementation independent.  
There is also a possibility to optimize a model by target device latency using ENOT neural architecture selection algorithm.  
Please, keep in mind that acceleration by device latency differs from acceleration by MACs.

| **Model**      | **MACs** | **Acceleration (MACs)** | PESQ score (the higher the better) |
|----------------|:--------:|:-----------------------:|:----------------------------------:|
| baseline       | 302.39 B |           1.0           |               3.381                |
| ENOT optimized | 120.95 B |           2.5           |               3.386                |

You can use `Baseline_model.pth` or `ENOT_optimized_model.pth` in the original repo by loading a model as generator in the following way:
```python
generator = torch.load("ENOT_optimized_model.pth")
```

Each of these two files contain a model object, saved by `torch.save`, so you can load them only from the original repository root because of imports.

If you want to book a demo, please contact us: enot@enot.ai .