Update app.py (#23)

- Update app.py (c24f22d5c5e7f25194c5f20f1e14b00b2996f635)

app.py

@@ -16,7 +16,7 @@ class TTS:
         global device
         device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
         torch.cuda.manual_seed(1234) if torch.cuda.is_available() else None
-        self.flowgenerator = Glow_model(n_vocab = 70, h_c= 192, f_c = 768, f_c_dp = 256, out_c = 80, k_s = 3, k_s_dec = 5, heads=2, layers_enc = 6).to(device)
+        self.flowgenerator = Glow_model(n_vocab = 70 if model_variant != '태연' else 73, h_c= 192, f_c = 768, f_c_dp = 256, out_c = 80, k_s = 3, k_s_dec = 5, heads=2, layers_enc = 6).to(device)
         self.voicegenerator = GAN_model().to(device)
         if model_variant == '감기걸린 은식':
             name = '1038_eunsik_01'
@@ -41,8 +41,8 @@ class TTS:
         self.voicegenerator.remove_weight_norm()
     
     def inference(self, input_text, noise_scale = 0.667, length_scale = 1.0):
-        filters = '([.,!?])'
-        sentence = re.sub(re.compile(filters), '', input_text)
+        filters = '([.,!?])' if st.session_state != '태연' else '([,])'
+        sentence = re.sub(re.compile(filters), '', input_text) 
         x = text_to_sequence(sentence)
         x = torch.autograd.Variable(torch.tensor(x).unsqueeze(0)).to(device).long()
         x_length = torch.tensor(x.shape[1]).unsqueeze(0).to(device)