Update app.py

app.py

@@ -53,7 +53,7 @@ def _clean_text(text, cleaner_names):
 
 def get_text(text, hps):
     text_norm = text_to_sequence(text, hps.data.text_cleaners)
-    if hps.data.add_blank:
+    if (hps.data.add_blank):
         text_norm = commons.intersperse(text_norm, 0)
     text_norm = torch.LongTensor(text_norm)
     return text_norm
@@ -96,6 +96,21 @@ def create_tab(tab_name):
         tts_output2 = gr.Audio(label="Output")
         tts_submit.click(lambda text, speaker_id: tts(text, speaker_id, tab_name), [tts_input1, tts_input2], [tts_output1, tts_output2])
 
+def tts_comparison(text, speaker_id):
+    result1 = tts(text, speaker_id, "Graphemes")
+    result2 = tts(text, speaker_id, "Graphemes_finetuned")
+    return result1[1], result2[1]
+
+def create_comparison_tab():
+    with gr.TabItem("Compare Models"):
+        gr.Markdown("### Compare TTS Models")
+        tts_input = gr.TextArea(label="Text in Walloon", value="")
+        tts_speaker = gr.Dropdown(label="Speaker", choices=["Male", "Female"], type="index", value="Male")
+        tts_submit = gr.Button("Generate", variant="primary")
+        tts_output1 = gr.Audio(label="Graphemes Output")
+        tts_output2 = gr.Audio(label="Graphemes Finetuned Output")
+        tts_submit.click(lambda text, speaker_id: tts_comparison(text, speaker_id), [tts_input, tts_speaker], [tts_output1, tts_output2])
+
 hps = utils.get_hparams_from_file("configs/vctk_base.json")
 
 app = gr.Blocks()
@@ -104,24 +119,21 @@ with app:
         """
         # First Text to Speech (TTS) for Walloon
         Based on VITS (https://github.com/jaywalnut310/vits).
-
         ## How to use:
         Write the text in graphemes. For faster inference, it is recommended to use short sentences.
         
         The quality of the results varies between male and female voice due to the limited data for female voice on this language. 
         For better results with male voice, use the models fully trained on Walloon.
         For better results with female voice, use the models trained on french and fine-tuned on Walloon.
-
         To try the version trained in phonemes follow the link below:
-
         https://huggingface.co/spaces/Pipe1213/VITS_Walloon_Phonemes
-
         ## Hint: Some sample texts are available at the bottom of the web site.
         """
     )
     with gr.Tabs():
         create_tab("Graphemes")
         create_tab("Graphemes_finetuned")
+        create_comparison_tab()
 
     gr.Markdown(
         """
@@ -135,4 +147,4 @@ with app:
         """
     )
 
-app.launch()
+app.launch()