Update demo.md

demo.md

@@ -51,7 +51,7 @@ def evaluate_model(ds, pipe, wer_metric):
         audio_sample = sample["audio"]
         transcription = pipe(audio_sample["array"])['text']
         # Keep only letter and spaces for evaluation
-        transcription = "".join([char for char in transcription if char.isalpha() or char.isspace()])
+        transcription = transcription.replace(",", "").replace(".", "").replace("!", "").replace("?", "")
         wer = wer_metric.compute(predictions=[transcription.upper()], references=[sample["text"].upper()])
         wer_scores.append(wer)
         wer_results.append({