Update README.md

README.md

@@ -71,17 +71,23 @@ Please notice that we encourage you to read our tutorials and learn more about [
 
 ```python
 from speechbrain.pretrained import SepformerSeparation as separator
+from speechbrain.pretrained.interfaces import fetch
 from speechbrain.pretrained.interfaces import SNREstimator as snrest
+
 import torchaudio
 
-# 1- Separate the mixture with a pretrained model (sepformer-whamr in this case)
-model = separator.from_hparams(source="speechbrain/sepformer-whamr", savedir='pretrained_models/sepformer-whamr2')
-est_sources = model.separate_file(path='speechbrain/sepformer-wsj02mix/test_mixture.wav')
+# 1- Download a test mixture
+fetch("test_mixture.wav", source="speechbrain/sepformer-whamr", savedir=".", save_filename="test_mixture.wav")
+
+# 2- Separate the mixture with a pretrained model (sepformer-whamr in this case)
+model = separator.from_hparams(source="speechbrain/sepformer-whamr", savedir='pretrained_models/sepformer-whamr')
+est_sources = model.separate_file(path='test_mixture.wav')
 
-# 2- Estimate the performance
+# 3- Estimate the performance
 snr_est_model = snrest.from_hparams(source="speechbrain/REAL-M-sisnr-estimator",savedir='pretrained_models/REAL-M-sisnr-estimator')
 mix, fs = torchaudio.load('test_mixture.wav')
 snrhat = snr_est_model.estimate_batch(mix, est_sources)
+print(snrhat) # Estimates are in dB
 
 ```