Create preprocess file

server/preprocess.py

@@ -0,0 +1,42 @@
+"""
+Util functions to process any incoming audio data to be processable by the model 
+"""
+import torch
+import torchaudio
+
+def process_raw_wav(wav, sample_rate, target_sample_rate=4800, wav_length=5):
+    num_samples = wav_length * target_sample_rate
+
+    wav = _resample(wav, sample_rate, target_sample_rate)
+    wav = _mix_down(wav)
+    wav = _cut(wav, num_samples)
+    wav = _pad(wav, num_samples)
+
+    return wav
+
+def _resample(wav, sample_rate, target_sample_rate):
+    if sample_rate != target_sample_rate:
+        resampler = torchaudio.transforms.Resample(sample_rate, target_sample_rate)
+        wav = resampler(wav)
+    
+    return wav
+
+def _mix_down(wav):
+    if wav.shape[0] > 1:
+        wav = torch.mean(wav, dim=0, keepdim=True)
+    
+    return wav
+
+def _cut(wav, num_samples):
+    if wav.shape[1] > num_samples:
+        wav = wav[:, :num_samples]
+    
+    return wav
+
+def _pad(wav, num_samples):
+    if wav.shape[1] < num_samples:
+        missing_samples = num_samples - wav.shape[1]
+        pad = (0, missing_samples)
+        wav = torch.nn.function.pad(wav, pad)
+    
+    return wav