update

examples/mpnet_aishell/yaml/config.yaml

@@ -13,11 +13,11 @@ compress_factor: 0.3
 num_tsconformers: 4
 beta: 2.0
 
-sample_rate: 16000
-segment_size: 32000
-n_fft: 400
-hop_size: 100
-win_size: 400
+sample_rate: 8000
+segment_size: 16000
+n_fft: 512
+hop_size: 80
+win_size: 200
 
 num_workers: 4
 

toolbox/torchaudio/models/mpnet/modeling_mpnet.py

@@ -251,7 +251,7 @@ def pesq_score(utts_r, utts_g, h):
     pesq_score = Parallel(n_jobs=30)(delayed(eval_pesq)(
                             utts_r[i].squeeze().cpu().numpy(),
                             utts_g[i].squeeze().cpu().numpy(),
-                            h.sampling_rate)
+                            h.sample_rate)
                           for i in range(len(utts_r)))
     pesq_score = np.mean(pesq_score)
 

toolbox/torchaudio/models/mpnet/utils.py

@@ -28,7 +28,7 @@ def pesq_score(utts_r, utts_g, h):
     pesq_score = Parallel(n_jobs=30)(delayed(eval_pesq)(
                             utts_r[i].squeeze().cpu().numpy(),
                             utts_g[i].squeeze().cpu().numpy(),
-                            h.sampling_rate)
+                            h.sample_rate)
                           for i in range(len(utts_r)))
     pesq_score = np.mean(pesq_score)