Update app.py

app.py

@@ -24,6 +24,11 @@ examples = [
         "movie, date, actor, tv-show, musician",
         True
     ],
+    [
+        "audio/personal_info.wav",
+        "address, name, phone-number",
+        True
+    ],
     [
         "audio/672-122797-0026.wav",
         "biological-classification, desire, demographic-group, object-category, relationship-role, reflexive-pronoun, furniture-type",
@@ -140,7 +145,7 @@ with gr.Blocks(title="WhisperNER v1") as demo:
         The [aiola/whisper-ner-tag-and-mask-v1](https://huggingface.co/aiola/whisper-ner-tag-and-mask-v1) model was finetuned from 
         the [aiola/whisper-ner-v1](https://huggingface.co/aiola/whisper-ner-v1) checkpoint using the NuNER dataset to perform joint audio transcription and NER tagging or NER masking. 
         The model was not trained on PII specific datasets, hence can perform general and open type entity masking. 
-        It should be further funetuned in order to be used for PII detection. The model was trained and evaluated only on English data. Check out the paper for full details.
+        It should be further finetuned in order to be used for PII detection. The model was trained and evaluated only on English data. Check out the paper for full details.
 
         ## Links
         * 📄 Paper: [WhisperNER: Unified Open Named Entity and Speech Recognition](https://arxiv.org/abs/2409.08107)