Update app.py

app.py

@@ -67,63 +67,28 @@ def number_to_words(number):
         return str(number)
 
 def normalize_text(text):
-    # Remove commas from numbers like 1,000,000
-    text = re.sub(r'(\d{1,3})(,\d{3})+', lambda m: m.group(0).replace(",", ""), text)
-
-    # Remove decimals (e.g., .00)
-    text = re.sub(r'\.\d+', '', text)
-
-    # Replace numbers with Somali words
-    def replace_num(match):
-        return number_to_words(match.group())
-
-    text = re.sub(r'\d+', replace_num, text)
-
-    # Replace special symbols
-    symbol_map = {
-        '$': 'doolar',
-        '=': 'egwal',
-        '+': 'balaas',
-        '#': 'haash'
-    }
-    for sym, word in symbol_map.items():
-        text = text.replace(sym, ' ' + word + ' ')
-
-    # Optional character normalization
+    numbers = re.findall(r'\d+', text)
+    for num in numbers:
+        text = text.replace(num, number_to_words(num))
     text = text.replace("KH", "qa").replace("Z", "S")
     text = text.replace("SH", "SHa'a").replace("DH", "Dha'a")
     text = text.replace("ZamZam", "SamSam")
-
     return text
 
 def tts(text):
-    paragraphs = text.strip().split("\n")
-    audio_list = []
-
-    for i, para in enumerate(paragraphs):
-        if not para.strip():
-            continue
-        norm_para = normalize_text(para)
-        inputs = tokenizer(norm_para, return_tensors="pt").to(device)
-        with torch.no_grad():
-            waveform = model(**inputs).waveform.squeeze().cpu().numpy()
-
-        # Add pause between paragraphs (only if it's not the last one)
-        if i < len(paragraphs) - 1:
-            pause = np.zeros(int(model.config.sampling_rate * 0.8))  # 0.8 seconds pause
-            audio_list.append(np.concatenate((waveform, pause)))
-        else:
-            audio_list.append(waveform)
-
-    final_audio = np.concatenate(audio_list)
+    text = normalize_text(text)
+    inputs = tokenizer(text, return_tensors="pt").to(device)
+    with torch.no_grad():
+        waveform = model(**inputs).waveform.squeeze().cpu().numpy()
     filename = "output.wav"
-    scipy.io.wavfile.write(filename, rate=model.config.sampling_rate, data=(final_audio * 32767).astype(np.int16))
+    scipy.io.wavfile.write(filename, rate=model.config.sampling_rate, data=(waveform * 32767).astype(np.int16))
     return filename
 
 gr.Interface(
     fn=tts,
-    inputs=gr.Textbox(label="Geli qoraal Soomaali ah", lines=10, placeholder="Ku qor 1 ama in ka badan paragraph..."),
+    inputs=gr.Textbox(label="Geli qoraal Soomaali ah"),
     outputs=gr.Audio(label="Codka TTS"),
     title="Somali TTS",
-    description="Ku qor qoraal Soomaaliyeed si aad u maqasho cod dabiici ah."
+    description="Ku qor qoraal Soomaaliyeed si aad u maqasho cod dabiici ah.",
 ).launch()
+