Create app.py

app.py

@@ -0,0 +1,32 @@
+from transformers import pipeline
+import gradio as gr
+from pyctcdecode import BeamSearchDecoderCTC
+
+#lmID = "aware-ai/german-lowercase-wiki-5gram"
+#decoder = BeamSearchDecoderCTC.load_from_hf_hub(lmID)
+emo = pipeline("audio-classification", model="Aniemore/wav2vec2-xlsr-53-russian-emotion-recognition")
+
+
+def transcribe(audio):
+    emotion = emo(audio)
+    return emotion
+
+def get_asr_interface():
+    return gr.Interface(
+        fn=transcribe, 
+        inputs=[
+            gr.inputs.Audio(source="microphone", type="filepath")
+        ],
+        outputs=[
+            "textbox",
+        ])
+        
+interfaces = [
+    get_asr_interface()
+]
+
+names = [
+    "ASR"
+]
+
+gr.TabbedInterface(interfaces, names).launch(server_name = "0.0.0.0", enable_queue=False)