Added app.py

app.py

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+import whisper
+
+import gradio as gr 
+import time
+
+
+# You can choose your model from - see it on readme file and update the modelname
+modelname = "large-v2"
+model = whisper.load_model(modelname)
+
+def SpeechToText(audio):
+    if audio == None : return "" 
+    time.sleep(1)
+
+    audio = whisper.load_audio(audio)
+    audio = whisper.pad_or_trim(audio)
+
+    #  Decode audio to Text
+    # options = whisper.DecodingOptions(fp16 = False)
+    result = model.transcribe(audio, language="hy")
+    return result["text"]
+
+
+gr.Interface(
+    title = 'OpenAI Whisper implementation on Gradio Web UI', 
+    fn=SpeechToText, 
+    
+    inputs=[
+        gr.Audio(source="microphone", type="filepath")
+    ],
+    outputs=[
+        "textbox",
+    ],
+    live=True
+).launch(
+    debug=False,
+    share=True
+)

requirements.txt

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+--extra-index-url https://download.pytorch.org/whl/cu116
+torch
+git+https://github.com/openai/whisper.git