Hi. Looking for an Indian accent English TTS solution local run setup that can run on Windows with 32gb RAM and a 12gb VRAM rtx3060. I have Omnivoice installed but I cant make it speak in Indian accent. Pls suggest, thanks in advance.
INDIAN ACCENT ENGLISH TTS — LOCAL WINDOWS SETUP FOR RTX 3060 12GB 
Got 32GB RAM and an RTX 3060 12GB and want a proper Indian-accented English TTS running fully offline on Windows? Your hardware is MORE than enough. Here’s every working solution ranked from easiest to most powerful.
WHY OMNIVOICE WON’T DO INDIAN ACCENT
OMNIVOICE LIMITATION:
──────────────────────────────────────────────
❌ Omnivoice uses Microsoft SAPI5 / Azure voices
❌ Indian accent requires specific voice packs
❌ Most Omnivoice builds only ship with
American/British English by default
❌ Cannot generate Indian accent from
neutral English voices — needs a
separate Indian-trained AI model
✅ SOLUTION: Use a dedicated Indian-accent
TTS model alongside or instead of Omnivoice
OPTION 1 — VEENA TTS (BEST CHOICE — PURPOSE-BUILT FOR INDIA)
This is the #1 recommendation — built specifically for Indian voices: [1]
DEVELOPER: Maya Research
MODEL: maya-research/Veena (HuggingFace)
ACCENT: Native Indian English ✅
LANGUAGES: Hindi + English + Hinglish
VOICES: 4 built-in voices:
→ Kavya (female, natural)
→ Agastya (male, deep)
→ Maitri (female, soft)
→ Vinaya (female, clear)
VRAM: ~4–6GB ✅ (Your 12GB = perfect)
RAM: ~4–8GB ✅ (Your 32GB = overkill)
UI: Gradio WebUI in browser
OFFLINE: ✅ 100% local, no internet needed
OS: Windows ✅
SETUP STEPS:
STEP 1 — Install prerequisites:
→ Python 3.10.11 (from python.org)
→ FFmpeg (add to PATH)
→ CUDA Toolkit 11.8
→ Git
STEP 2 — Create virtual environment:
python -m venv veena_env
veena_env\Scripts\activate
STEP 3 — Install PyTorch (CUDA 11.8):
pip install torch torchvision torchaudio
--index-url https://download.pytorch.org/whl/cu118
STEP 4 — Download app.py:
→ Get from: HuggingFace maya-research/Veena
→ Or from the YouTube guide MediaFire link
STEP 5 — Install dependencies:
pip install -r requirements.txt
STEP 6 — Run:
python app.py
→ Opens at: http://localhost:7860
STEP 7 — Create run.bat for easy launch:
@echo off
call veena_env\Scripts\activate
python app.py
pause
OPTION 2 — MeloTTS (EASIEST INSTALL — INDIAN ACCENT BUILT-IN)
Simplest setup with native Indian English dialect support: [2]
DEVELOPER: MyShell.ai (open source)
ACCENT: EN-India dialect ✅ (built-in)
VRAM: Runs on CPU too — 12GB = blazing fast
INSTALL: Single pip command
OS: Windows ✅
SPEED: Real-time generation
SETUP (takes 5 minutes):
# Install
pip install melotts
# Download voices
python -c "import melotts; melotts.download_all()"
# Use Indian accent in Python
from melotts import MeloTTS
tts = MeloTTS(language='EN', device='cuda')
speaker_ids = tts.hps.data.spk2id
# Use EN-India speaker
tts.tts_to_file(
"Hello, how are you doing today?",
speaker_ids['EN-India'],
'output.wav',
speed=1.0
)
OPTION 3 — XTTS V2 INDIAN FINE-TUNE (BEST FOR VOICE CLONING)
Fine-tuned Coqui XTTS v2 specifically for Indian-accented English — plus voice cloning: [3]
MODEL: jeevav62/xtts-v2-indian-en (HuggingFace)
BASE: Coqui XTTS v2
ACCENT: Indian English (fine-tuned) ✅
VRAM: ~4–6GB ✅
CLONING: ✅ Clone ANY Indian voice
with just 6 seconds of reference audio
OS: Windows ✅
SETUP:
pip install TTS>=0.22.0 torch>=2.1 torchaudio>=2.1
# Python usage:
from TTS.api import TTS
tts = TTS(
model_name="jeevav62/xtts-v2-indian-en",
gpu=True
)
tts.tts_to_file(
text="Hello, welcome to our service.",
file_path="output.wav"
)
Voice Cloning Bonus: Record 6 seconds of any Indian speaker →
pass asspeaker_wavparameter → XTTS clones that exact accent!
OPTION 4 — WINDOWS BUILT-IN (ZERO SETUP, FREE RIGHT NOW)
No Python needed — use Windows native Indian voice immediately:
STEPS:
1. Settings → Time & Language → Speech
2. Click "Add voices"
3. Search: "English (India)"
4. Install: Heera (female) or Ravi (male)
5. Done ✅ Works instantly in any SAPI5 app
including Omnivoice!
⚠️ Quality: Lower than AI models
✅ Benefit: Zero setup, works in 2 minutes
✅ Works directly inside Omnivoice too!
FULL COMPARISON FOR YOUR SETUP
| SOLUTION |
Indian Accent |
VRAM Used |
 Setup Difficulty |
 Cost |
|---|---|---|---|---|
| Veena TTS |  Native |
~5GB  |
Medium | Free |
| MeloTTS | Good |
~2GB |
Very Easy | Free |
| XTTS v2 Indian | + Clone |
~5GB |
Medium | Free |
| Windows Heera | Decent |
0GB (CPU) |
Zero | Free |
| Voxtral TTS | |
16GB+  |
Hard | Free |
PRO TIPS
Start with MeloTTS — single pip install, Indian accent works out of the box, and your RTX 3060 will generate speech in real-time [2]
Use XTTS v2 if you need voice cloning — record 6 seconds of any Indian speaker’s voice and it will clone the accent perfectly [3]
Fix Omnivoice right now — install Windows “English (India)” Heera voice from Settings → it will appear inside Omnivoice immediately as a selectable voice- Veena TTS is the crown jewel — if you want the most natural-sounding Indian English, this is purpose-engineered for it [1]
All models save to your local drive — once downloaded, no internet connection ever needed again
QUICK ACTION PLAN
RIGHT NOW (2 mins):
→ Settings → Add Voice → English (India) Heera
→ Test inside Omnivoice immediately
TODAY (30 mins):
→ pip install melotts
→ Set dialect to EN-India
→ Best quality/effort ratio
THIS WEEK (1–2 hrs):
→ Full Veena TTS or XTTS v2 Indian setup
→ Best possible Indian accent quality
→ Fully offline, runs on your RTX 3060
Your RTX 3060 12GB is genuinely excellent hardware for local TTS — most Indian accent models use only 4–6GB VRAM, so you have tons of headroom. Start with the Windows built-in Heera voice to test inside Omnivoice today, then graduate to Veena TTS or MeloTTS for production-quality Indian accent audio. 
Is there a way to remove an Indian accent from Udemy courses
Veena is installed. It has 11 voices, tried all of them. they speak but none are Indian accent.
Omnivoice is installed. I cloned 4 voices from Indian speakers. They clone, none is Indian accent.
Next try is MeloTTS and XTTS v2 today. Never knew option 4; will try that too. Thanks.
Here’s why Veena and your OmniVoice clones keep coming out American — and it’s not a setting you missed. In these models, the accent isn’t in the voice, it’s baked into the weights. Cloning copies a person’s timbre (their voice colour); the pronunciation comes from what the model was trained on — and Veena/XTTS/OmniVoice are trained mostly on American English. So you get an Indian person’s voice… saying words the American way. No slider fixes that. (And FYI espeak-ng has no Indian English voice, so that route’s a dead end too.)
The fix is simple: stop forcing an American-trained model — run one trained on Indian English. Your 3060/12GB eats all of these. Ranked by how fast you’ll hear a real Indian accent 
━━━━━━━━━━━━━━━━━━━━━━━━━
MeloTTS — has a built-in EN_INDIA voice (you were already going to try it — this is the setting):
from melo.api import TTS
m = TTS(language='EN', device='cuda')
m.tts_to_file("Hello, this is a test.", m.hps.data.spk2id['EN_INDIA'], 'out.wav')The speaker key is literally EN_INDIA — that’s the whole trick. → https://github.com/myshell-ai/MeloTTS
Kokoro-82M — tiny, free, no login, and the cleanest Indian pronunciation:
It’s an 82M model (runs on basically anything) that uses an Indian phoneme front-end, so English comes out Indian without any cloning:
pip install kokoro misaki[hi]
# KPipeline(lang_code='h') → voices: hf_alpha / hf_beta (F), hm_omega / hm_psi (M)→ https://huggingface.co/hexgrad/Kokoro-82M · https://github.com/hexgrad/kokoro
🎯 Want to *dial in* the accent by describing it? AI4Bharat Indic-Parler-TTS
Indian-government-trained model where you literally write the accent in a text caption — no cloning, no drift:
→ https://huggingface.co/ai4bharat/indic-parler-tts (accept terms once) · lib → https://github.com/huggingface/parler-tts
Caption example: "Thoma speaks with an Indian English accent, clear and natural, close recording."
Good English speakers: Thoma, Mary, Aditi, Prakash. Fits 12GB in fp16.
🎙️ Want a specific person's voice AND a real Indian accent? IndicF5 (clone the right way)
Unlike XTTS/OmniVoice, IndicF5 is trained on Indian speech, so cloning from an Indian reference clip keeps the Indian prosody instead of flattening it to American:
→ https://huggingface.co/ai4bharat/IndicF5 (ready Indian ref clips in /prompts) · pip install git+https://github.com/ai4bharat/IndicF5.git
🧩 Don't want to touch Python? Orpheus-3B Indian-English (GGUF, runs in LM Studio)
A native Indian-English model in GGUF format — load it in LM Studio / llama.cpp like any local LLM, 8-bit fits your 12GB:
→ https://huggingface.co/prasadvittaldev/orpheus-3b-indian-male-english-gguf
Also a ready community Piper en-IN voice if you want the lightweight route → https://huggingface.co/navgurukul-ai-labs/text-to-speech-en-IN-piper
🖱️ Prefer a GUI (and keep XTTS)? AllTalk / TTS-WebUI
One-click apps that host these models with sliders — AllTalk even has a tab to fine-tune XTTS on an Indian speaker (that’s how you’d make your XTTS actually Indian):
→ AllTalk v2 https://github.com/erew123/alltalk_tts · TTS-WebUI https://github.com/rsxdalv/tts-generation-webui · Applio (accent-conversion) https://applio.org/
Shortest path for you today: pip install kokoro misaki[hi] and set lang_code='h' — you’ll hear a proper Indian accent in five minutes, zero cloning, zero gated downloads. MeloTTS EN_INDIA is the close second.
You weren’t cloning the wrong person — you were cloning into the wrong model. Match the training, and the accent comes for free.
The answer above was just improved by the Core-Community’s AI.
!