adds mic or file

app.py

@@ -5,18 +5,48 @@ model = nemo_asr.models.ASRModel.restore_from("CnLgGm025_SpeUni1024_DI_EATL.nemo
 model.eval()
 
 
-def transcribe(audio_file):
-    # import speech_recognition as sr
-    # r = sr.Recognizer()
-    # with sr.AudioFile(audio_file) as source:
-    #     audio = r.record(source)
-    # return r.recognize_google(audio)
-    t = model.transcribe([audio_file])
-    return t[0]
-
-
-gr.Interface(
-    transcribe,
-    inputs=gr.inputs.Audio(source="microphone", type="filepath"),
-    outputs="text",
-).launch()
+def transcribe(audio_mic, audio_file, models_names):
+    # transcribe audio_mic and audio_file separately
+    # because transcribe() fails is path is empty
+    transcription_mic = "\n".join(
+        [
+            f"{model_name} => {model.transcribe([audio_mic])[0]}"
+            for model_name in models_names
+        ]
+        if audio_mic
+        else ""
+    )
+    transcription_file = "\n".join(
+        [
+            f"{model_name} => {model.transcribe([audio_file])[0]}"
+            for model_name in models_names
+        ]
+        if audio_file
+        else ""
+    )
+    return transcription_mic, transcription_file
+
+
+selection = ["a", "b", "c"]
+
+demo = gr.Blocks()
+
+with demo:
+    models_names = gr.CheckboxGroup(selection)
+    with gr.Row():
+        audio_mic = gr.Audio(source="microphone", type="filepath", label="Microphone")
+        audio_file = gr.Audio(source="upload", type="filepath", label="File")
+
+    with gr.Row():
+        output_mic = gr.TextArea(label="Microphone Transcription")
+        output_file = gr.TextArea(label="Audio Transcription")
+
+    b1 = gr.Button("Transcribe")
+
+    b1.click(
+        transcribe,
+        inputs=[audio_mic, audio_file, models_names],
+        outputs=[output_mic, output_file],
+    )
+
+demo.launch()