Update app.py

app.py

@@ -21,11 +21,19 @@ gos_text2speech = Text2Speech.from_pretrained(
   vocoder_tag="parallel_wavegan/ljspeech_parallel_wavegan.v3"
 )
 
+westerkwartiers_text2speech = Text2Speech.from_pretrained(
+  model_tag="https://huggingface.co/ahnafsamin/FastSpeech2-gronings-westerkwartiers/resolve/main/tts_train_fastspeech2_raw_char_tacotron_train.loss.ave.zip",
+  vocoder_tag="parallel_wavegan/ljspeech_parallel_wavegan.v3"
+)
+
 def inference(text,lang):
   with torch.no_grad():
       if lang == "gronings":
           wav = gos_text2speech(text)["wav"]
           scipy.io.wavfile.write("out.wav", gos_text2speech.fs , wav.view(-1).cpu().numpy())
+      elif lang == "gronings westerkwartiers":
+          wav = westerkwartiers_text2speech(text)["wav"]
+          scipy.io.wavfile.write("out.wav", westerkwartiers_text2speech.fs , wav.view(-1).cpu().numpy())
 
   return  "out.wav", "out.wav"
 
@@ -37,7 +45,7 @@ examples = [
 
 gr.Interface(
     inference,
-    [gr.inputs.Textbox(label="input text", lines=3), gr.inputs.Radio(choices=["gronings"], type="value", default="gronings", label="language")], 
+    [gr.inputs.Textbox(label="input text", lines=3), gr.inputs.Radio(choices=["gronings", "gronings westerkwartiers"], type="value", default="gronings", label="language")], 
     [gr.outputs.Audio(type="file", label="Output"), gr.outputs.File()],
     title=title,
     examples=examples