Corrections on the transcriptions

app.py

@@ -31,7 +31,7 @@ def compute_wer_table(audio, text):
     for model in model_name:
         pipe = pipeline("automatic-speech-recognition", model=model_name[model])
         transcription = pipe(audio_input)['text']
-        transcription = transcription.replace(",", "").replace(".", "")
+        transcription = transcription.replace(",", "").replace(".", "").replace("?", "").replace("!", "")
         trans.append(transcription)
         wer = wer_metric.compute(predictions=[transcription.upper()], references=[text.upper()])
         wer_scores.append(wer)