Update app.py

app.py

@@ -6,10 +6,10 @@ import numpy as np
 
 
 tts_model = TTSInferencing.from_hparams(source="./",
-                                        hparams_file='./hyperparams.yaml',
-                                        pymodule_file='./module_classes.py',
-                                        # savedir="./",
-                                        )
+                                    hparams_file='./hyperparams.yaml',
+                                    pymodule_file='./module_classes.py',
+                                    # savedir="./",
+                                    )
 
 hifi_gan = HIFIGAN.from_hparams(source="speechbrain/tts-hifigan-ljspeech")
 
@@ -18,18 +18,18 @@ hifi_gan = HIFIGAN.from_hparams(source="speechbrain/tts-hifigan-ljspeech")
 # Input text
 text = st.text_area("Enter your text here")
 
-if st.button("To Speech"):
-    if text:
-        mel_outputs = tts_model.encode_batch(text)
-        waveforms = hifi_gan.decode_batch(mel_outputs)
-    
-        waveform =  waveforms[0].squeeze(1).numpy()
-    
-        # Normalize the waveform to the range [-1, 1] if necessary
-        if np.max(np.abs(waveform)) > 1.0:
-            waveform /= np.max(np.abs(waveform))
-    
-        # Display the audio widget to play the synthesized speech
-        st.audio(waveform, format="audio/wav", sample_rate = 22050)
-    else:
-        st.error("Please enter text to get the speech.")
+
+if text:
+    mel_outputs = tts_model.encode_batch(text)
+    waveforms = hifi_gan.decode_batch(mel_outputs)
+
+    waveform =  waveforms[0].squeeze(1).numpy()
+
+    # Normalize the waveform to the range [-1, 1] if necessary
+    if np.max(np.abs(waveform)) > 1.0:
+        waveform /= np.max(np.abs(waveform))
+
+    # Display the audio widget to play the synthesized speech
+    st.audio(waveform, format="audio/wav", sample_rate = 22050)
+else:
+    st.error("Please enter text to get the speech.")