Little function to deal with no scoring

helpers.py

@@ -123,9 +123,17 @@ def crear_diccionario(json_data):
         
         # Iteramos sobre las palabras del segmento
         for palabra in palabras:
+
             # Obtenemos los valores de la palabra
             word = palabra['word']
-            score = palabra['score']
+            if 'score'not in palabra.keys():
+                print(segmento)
+                print(palabra)
+                # Agregamos el score por defecto
+                palabra['score'] = 0.5
+            else:
+                score = palabra['score']
+
             
             # Agregamos los valores al diccionario
             diccionario['start_time'].append(start_time)

transcription.py

@@ -46,7 +46,7 @@ def doWhisperX(audio_file, whisper_model="large-v2", language="es"):
 
     audio = whisperx.load_audio(audio_file)
     result_whisper = model.transcribe(audio, language=language, batch_size=batch_size)
-    print(result_whisper["segments"]) # before alignment
+    #print(result_whisper["segments"]) # before alignment
 
     # delete model if low on GPU resources
     # import gc; gc.collect(); torch.cuda.empty_cache(); del model
@@ -55,7 +55,7 @@ def doWhisperX(audio_file, whisper_model="large-v2", language="es"):
     model_a, metadata = whisperx.load_align_model(language_code=result_whisper["language"], device=device)
     result_aligned = whisperx.align(result_whisper["segments"], model_a, metadata, audio, device, return_char_alignments=False)
 
-    print(result_aligned) # after alignment
+    #print(result_aligned) # after alignment
 
     # delete model if low on GPU resources
     # import gc; gc.collect(); torch.cuda.empty_cache(); del model_a