Update wav2vec_aligen.py

wav2vec_aligen.py

@@ -12,7 +12,7 @@ device = 'cuda' if torch.cuda.is_available() else 'cpu'
 torch.random.manual_seed(0); 
 # protobuf==3.20.0
 
-model_name = "arslanarjumand/wav2vec-reptiles"
+model_name = "arslanarjumand/wav2vec-read_aloud"
 processor = AutoFeatureExtractor.from_pretrained(model_name)
 model = Wav2Vec2BertForSequenceClassification.from_pretrained(model_name).to(device)
 # model = BetterTransformer.transform(model)
@@ -28,10 +28,17 @@ def get_emissions(input_values, model):
     results = model(input_values,).logits[0]
     return results
 
-def vlaidate_range(score):
-    score = score if score <= 90 else 90
-    score = score if score >= 10 else 10
-    return score
+def validate_range(value):
+    value = 10 + value * 80
+    if value > 90:
+        return 90
+        
+    if value < 50 and value > 10:
+        value = value - 5
+    elif value < 10:
+        value = 10
+    else: None
+    return int(value)
 
 def speaker_pronunciation_assesment(audio_path):
     input_values = load_audio(audio_path, processor)