Add application file

app.py

@@ -0,0 +1,52 @@
+import gradio as gr
+
+app = gr.Blocks()
+
+
+
+mic_mode = gr.Interface(
+    fn=inference,
+    inputs=gr.Audio(sources="microphone", type='filepath', label="Record Your Lecture"),
+    outputs=gr.Textbox(label="Transcription Output"),
+    title="🎙️ Live Lecture Transcription",
+    description="Record through your mic. When you're done, hit stop and wait a moment. Feel free to trim the recording. Then, hit Submit!",
+    examples=[],
+)
+
+
+upload_mode = gr.Interface(
+    fn=inference,
+    inputs=gr.Audio(sources="upload", type='filepath', label="Upload Your Lecture Recording"),
+    outputs=gr.Textbox(label="Transcription Output"),
+    title="📂 Lecture Recording Transcription",
+    description="Have a recorded lecture? Upload the audio file here, and it'll be transcribed in seconds!",
+)
+
+
+with app:
+    gr.Markdown(
+        """
+        # Lecture Transcription 📝
+        
+        Welcome to **Lecture Transcription**, the go-to tool for transcribing lectures accurately. Whether you’re attending a live lecture or revisiting a recorded one, this app will ensure you don’t miss a single detail.
+
+        ## How It Works
+        - **Recording Mode:** Record the lecture as it happens. When you stop, your transcription will be generated.
+        - **Upload Mode:** Upload your pre-recorded lecture audio files, and receive a precise transcription. Supports various audio formats including WAV, MP3, and more.
+
+        ## Optimized for Technical Oration
+        Under the hood, this is a Wav2Vec2 model fine-tuned on the TED-Lium dataset. It's well-versed for 
+        accurately transcribing technical speech.
+  
+        
+        **Never miss a word with Lecture Transcription!**
+        """
+    )
+    # Add a Tabbed Interface for different modes
+    gr.TabbedInterface(
+        [mic_mode, upload_mode],
+        ["🎙️ Record & Transcribe", "📂 Upload & Transcribe"]
+    )
+
+# Launch the app
+app.launch()