Create app.py

app.py

@@ -0,0 +1,35 @@
+# Let's get pipelines from transformers
+from transformers import pipeline
+# Let's import Gradio
+import gradio as gr
+
+# Let's set up the model
+model = pipeline("automatic-speech-recognition", model="moraxgiga/audio_test")
+title = "Audio2Text"
+description = "Record your audio in English and send it in order to received a transcription"
+
+
+# Function
+def transcribe(audio):
+  # Let's invoke "model" defined above
+  text = model(audio)["text"]
+  return text
+
+
+# Interface Set-Up
+'''gr.Interface(
+    fn=transcribe,
+    inputs=[gr.Audio(source="microphone", type="filepath")],
+    title="Audio-to-text",
+    description="kat enterprises llc demo text-to-speech model",
+    outputs=["textbox"]
+).launch()
+'''
+
+demo = gr.Interface(fn=transcribe ,
+                    inputs=[gr.Audio(source="microphone", type="filepath")],
+                    outputs=[gr.Textbox(label="Result", lines=3)],
+                    title="Audio-to-text",
+                    description="kat enterprises llc demo text-to-speech model"
+                   )
+demo.launch()