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import gradio as gr
import torch
import numpy as np
import scipy.io.wavfile
from transformers import VitsModel, AutoTokenizer
import re
# Load model and tokenizer
model = VitsModel.from_pretrained("Somali-tts/somali_tts_model")
tokenizer = AutoTokenizer.from_pretrained("saleolow/somali-mms-tts")
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model.to(device)
model.eval()
# Numbers in Somali
number_words = {
0: "eber", 1: "koow", 2: "labo", 3: "seddex", 4: "afar", 5: "shan",
6: "lix", 7: "todobo", 8: "sideed", 9: "sagaal", 10: "toban",
11: "toban iyo koow", 12: "toban iyo labo", 13: "toban iyo seddex",
14: "toban iyo afar", 15: "toban iyo shan", 16: "toban iyo lix",
17: "toban iyo todobo", 18: "toban iyo sideed", 19: "toban iyo sagaal",
20: "labaatan", 30: "sodon", 40: "afartan", 50: "konton",
60: "lixdan", 70: "todobaatan", 80: "sideetan", 90: "sagaashan",
100: "boqol", 1000: "kun"
}
# Shortcut dictionary
shortcut_map = {
"asc": "asalaamu caleykum",
"wcs": "wacaleykum salaam",
"fcn": "fiican",
"xld": "xaaladda ka waran",
"kwrn": "kawaran",
"scw": "salalaahu caleyhi wa salam",
"alx": "alxamdu lilaahi",
"m.a": "maasha allah",
"sthy": "side tahey",
"sxp": "saaxiib"
}
# Countries dictionary (English to Somali)
country_map = {
"somalia": "Soomaaliya",
"ethiopia": "Itoobiya",
"kenya": "Kenya",
"djibouti": "Jabuuti",
"sudan": "Suudaan",
"Yeman": "yemaan",
"uganda": "Ugaandha",
"tanzania": "Tansaaniya",
"egypt": "Masar",
"libya": "Liibiya",
"algeria": "Aljeeriya",
"morocco": "Morooko",
"tunisia": "Tuniisiya",
"eritrea": "Eriteriya",
"malawi": "Malaawi",
"English": "ingiriis",
"Spain": "isbeen",
"Brazil": "baraasiil",
"niger": "Niyjer",
"Italy": "itaaliya",
"united states": "Maraykanka",
"china": "Shiinaha",
"india": "Hindiya",
"russia": "Ruushka",
"Saudi Arabia": "Sucuudi Carabiya",
"germany": "Jarmalka",
"france": "Faransiiska",
"japan": "Jabaan",
"canada": "Kanada",
"australia": "Australia"
}
def number_to_words(number):
number = int(number)
if number < 20:
return number_words[number]
elif number < 100:
tens, unit = divmod(number, 10)
return number_words[tens * 10] + (" iyo " + number_words[unit] if unit else "")
elif number < 1000:
hundreds, remainder = divmod(number, 100)
part = (number_words[hundreds] + " boqol") if hundreds > 1 else "boqol"
if remainder:
part += " iyo " + number_to_words(remainder)
return part
elif number < 1000000:
thousands, remainder = divmod(number, 1000)
words = []
if thousands == 1:
words.append("kun")
else:
words.append(number_to_words(thousands) + " kun")
if remainder >= 100:
hundreds, rem2 = divmod(remainder, 100)
if hundreds:
boqol_text = (number_words[hundreds] + " boqol") if hundreds > 1 else "boqol"
words.append(boqol_text)
if rem2:
words.append("iyo " + number_to_words(rem2))
elif remainder:
words.append("iyo " + number_to_words(remainder))
return " ".join(words)
elif number < 1000000000:
millions, remainder = divmod(number, 1000000)
words = []
if millions == 1:
words.append("milyan")
else:
words.append(number_to_words(millions) + " milyan")
if remainder:
words.append(number_to_words(remainder))
return " ".join(words)
else:
return str(number)
def normalize_text(text):
# ➤ Beddel ereyga zamzam dhammaan noocyadiisa (bilow, dhex, dhammaad)
text = re.sub(r'(?i)(?<!\w)zamzam(?!\w)', 'samsam', text)
# ➤ Bedel shortcuts - eray kasta oo qoraalka ku jira beddel
def replace_shortcuts(match):
word = match.group(0).lower()
return shortcut_map.get(word, word)
pattern = re.compile(r'\b(' + '|'.join(re.escape(k) for k in shortcut_map.keys()) + r')\b', re.IGNORECASE)
text = pattern.sub(replace_shortcuts, text)
# ➤ Bedel magacyada waddamada
def replace_countries(match):
word = match.group(0).lower()
return country_map.get(word, word)
country_pattern = re.compile(r'\b(' + '|'.join(re.escape(k) for k in country_map.keys()) + r')\b', re.IGNORECASE)
text = country_pattern.sub(replace_countries, text)
# ➤ Ka saar tirooyin leh koma iyo tobanle
text = re.sub(r'(\d{1,3})(,\d{3})+', lambda m: m.group(0).replace(",", ""), text)
text = re.sub(r'\.\d+', '', text)
# ➤ Beddel tirooyin (1 → koow, iwm.)
def replace_num(match):
return number_to_words(match.group())
text = re.sub(r'\d+', replace_num, text)
# ➤ Beddel calaamadaha khaaska ah
symbol_map = {
'$': 'doolar',
'=': 'egwal',
'+': 'balaas',
'#': 'haash'
}
for sym, word in symbol_map.items():
text = text.replace(sym, ' ' + word + ' ')
# ➤ Beddel xarfo khaas ah
text = text.replace("KH", "qa").replace("Z", "S")
text = text.replace("SH", "SHa'a").replace("DH", "Dha'a")
# ➤ Haddii jumladda ku dhammaato zamzam ama samsam, ku dar " m" (silent m)
if re.search(r'(?i)(zamzam|samsam)[\s\.\,\!\?]*$', text.strip()):
text += " m"
return text
def tts(text):
paragraphs = text.strip().split("\n")
audio_list = []
max_chars = 500 # Qiyaasta ugu badan 2 daqiiqo
warn_msg = ""
for i, para in enumerate(paragraphs):
para = para.strip()
if not para:
continue
if len(para) > max_chars:
warn_msg += f"❗ Qaybta {i+1} aad ayaa ka badan 2 daqiiqo. Waan kala jaray.\n"
sub_parts = [para[j:j+max_chars] for j in range(0, len(para), max_chars)]
else:
sub_parts = [para]
for part in sub_parts:
norm_para = normalize_text(part)
inputs = tokenizer(norm_para, return_tensors="pt").to(device)
with torch.no_grad():
waveform = model(**inputs).waveform.squeeze().cpu().numpy()
pause = np.zeros(int(model.config.sampling_rate * 0.8)) # 0.8s pause
audio_list.append(np.concatenate((waveform, pause)))
final_audio = np.concatenate(audio_list)
filename = "output.wav"
scipy.io.wavfile.write(filename, rate=model.config.sampling_rate, data=(final_audio * 32767).astype(np.int16))
if warn_msg:
print(warn_msg)
return filename
# Gradio interface
gr.Interface(
fn=tts,
inputs=gr.Textbox(label="Geli qoraal Soomaali ah", lines=10, placeholder="Ku qor 1 ama in ka badan paragraph..."),
outputs=gr.Audio(label="Codka TTS"),
title="Somali TTS",
description="Ku qor qoraal Soomaaliyeed si aad u maqasho cod dabiici ah. Qoraalka ha ka badnaan 2 daqiiqo per jumlad."
).launch()
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