Update app.py

app.py

@@ -14,9 +14,38 @@ import utils
 from data_utils import TextAudioLoader, TextAudioCollate, TextAudioSpeakerLoader, TextAudioSpeakerCollate
 from models import SynthesizerTrn
 from text.symbols import symbols
-from text import text_to_sequence
+#from text import text_to_sequence
 from scipy.io.wavfile import write
 
+# symbols = symbols_gra # change this later 
+_symbol_to_id = {s: i for i, s in enumerate(symbols)}
+_id_to_symbol = {i: s for i, s in enumerate(symbols)}
+
+def text_to_sequence(text, cleaner_names):
+  '''Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
+    Args:
+      text: string to convert to a sequence
+      cleaner_names: names of the cleaner functions to run the text through
+    Returns:
+      List of integers corresponding to the symbols in the text
+  '''
+  sequence = []
+
+  clean_text = _clean_text(text, cleaner_names)
+  for symbol in clean_text:
+    symbol_id = _symbol_to_id[symbol]
+    sequence += [symbol_id]
+  return sequence
+
+def _clean_text(text, cleaner_names):
+  for name in cleaner_names:
+    cleaner = getattr(cleaners, name)
+    if not cleaner:
+      raise Exception('Unknown cleaner: %s' % name)
+    text = cleaner(text)
+  return text
+
+
 def get_text(text, hps):
     text_norm = text_to_sequence(text, hps.data.text_cleaners)
     if hps.data.add_blank:
@@ -77,20 +106,33 @@ with app:
         Based on VITS (https://github.com/jaywalnut310/vits).
 
         Write the text in phonemes or graphemes depending on the model.
+        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 graphemes follow the link below:
+
+        https://huggingface.co/spaces/Pipe1213/VITS_Walloon_Graphemes
 
-        For faster inference speed it is recommended to use short sentences.
+        
+        ## Hint: Some sample texts are available at the bottom of the web site.
+        ## Hint: For faster inference speed it is recommended to use short sentences.
         """
     )
     with gr.Tabs():
         create_tab("Phonemes_finetuned")
+        create_tab("Phonemes(not working yet!!!)")
 
     gr.Markdown(
         """
         ### Examples
-        | Input Text | Speaker | Input Method  |
-        |------------|---------|---------------|
-        | li biːç ɛ l sɔlja ɛstẽ ki s maʁɡajẽ pɔ sawɛ kiː ski , dɛ døː , ɛstøː l py fwaʁ . m ɛ̃ s koː la , la k i vɛjɛ õ tsminɔː k aʁivef pjim pjam , d ɛ̃ õ bja nuː tsoː paltɔ .  | Female | Phonemes |
-        | Li bijhe et l’ solea estént ki s’ margayént po sawè kî çki, des deus, esteut l’ pus foirt. Mins ç’ côp la, la k’ i veyèt on tchminåd k' arivéve pyim piam, dins on bea noû tchôd paltot.  | Male | Graphemes |
+        | Input Text | Speaker |
+        |------------|---------|
+        | li biːç ɛ l sɔlja ɛstẽ ki s maʁɡajẽ pɔ sawɛ kiː ski , dɛ døː , ɛstøː l py fwaʁ . m ɛ̃ s koː la , la k i vɛjɛ õ tsminɔː k aʁivef pjim pjam , d ɛ̃ õ bja nuː tsoː paltɔ .  | Female |
+        | ɛl m õ ʁɛspõdu ,  duvẽ ɔːʁẽ n pøː d õ tsapja . | Male |
+        | dɔ koː , dz a dvu tswɛzi ɛn oːt mɛstiː , dz ast apʁ ɛ̃ a mõne dɛz avjõ .| Female |
         """
     )