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๐Ÿ”ฅ Free Alternative to ElevenLabs and Cloud Whisper APIs14.2k GitHub Stars๐Ÿ’ป C++ / Python TerminalC++

Sherpa-ONNXby k2-fsa

Sherpa-ONNX runs speech recognition, text-to-speech, speaker diarization, and audio separation locally using ONNX Runtime without needing an internet connection. It's also a popular Free Alternative to ElevenLabs and Cloud Whisper APIs for creators who don't want to pay a monthly subscription.

โ“

What Is Sherpa-ONNX?

New to GitHub repos? Here's what this actually does, in plain language:

Bhai, agar aapko Bina internet ke fast captions generate karne hain ya local voice-over chahiye bina cloud subscription ke, toh yeh tool ekdum solid option hai.

โœ“Completely offline speech-to-text and text-to-speech processing
โœ“Supports speaker diarization and voice activity detection (VAD)
โœ“Runs on low-power edge devices like Raspberry Pi as well as mobile
โœ“Zero API costs and complete data privacy for client projects
โš–๏ธ

Strengths, Limitations & Is It Safe to Install?

An honest breakdown before you install anything on your PC:

โœ… What It Does Well

  • Blazing fast inference speeds on CPU because it relies on C++ and ONNX Runtime
  • No internet dependency means zero data leakage when handling sensitive client audio
  • Cross-platform support spans Android, iOS, Windows, and Linux smoothly

โŒ What It Can't Do / Limitations

  • Setting up models and compilation requires comfort with command-line tools
  • Pre-trained Indian language models might need manual downloading and path configuration
  • Not a drag-and-drop desktop app, so non-technical editors will face a steep learning curve

๐Ÿ›ก๏ธ Is It Safe to Install?

The software itself is safe open-source code from a reputable repo, but using text-to-speech or voice cloning features requires ethical handling of individuals' likeness and voice data to avoid impersonation issues.

๐Ÿ–ฅ๏ธ

Hardware & PC System Requirements

Check if your laptop / PC can run Sherpa-ONNX smoothly:

Minimum VRAM / GPU
Integrated Graphics / 2GB VRAM
Recommended GPU
4GB+ Dedicated GPU VRAM
System RAM Required
8GB - 16GB RAM
Free SSD Disk Space
5GB - 15GB Free SSD Space
Supported Platforms:๐ŸชŸ Windows 10 / 11๐ŸŽ macOS (Apple Silicon M1/M2/M3)๐Ÿง Linux (Ubuntu CUDA)

โšก 1-Click Setup Commands for Sherpa-ONNX

Copy & paste in Terminal or Command Prompt:
Python / Pip / Git Command:pip install sherpa-onnx
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๐Ÿ“–

Beginner Installation Guide (Windows & Mac)

Straightforward step-by-step installation instructions for Windows and macOS systems:

๐Ÿ’ป Windows Install Steps:

  1. Step 1: Press Win + R keys together, type cmd and hit Enter to open Command Prompt.
  2. Step 2: Copy the pip install sherpa-onnx command from the top banner.
  3. Step 3: Right-click in Command Prompt to paste the command and press Enter. Installation complete!

๐Ÿ Mac Install Steps (Apple Silicon & Intel):

  1. Step 1: Press Cmd + Space, type Terminal and hit Enter.
  2. Step 2: Copy the pip install sherpa-onnx command from the top banner.
  3. Step 3: Paste into Terminal and press Enter. If Mac blocks opening: Go to System Settings > Privacy & Security > Click "Open Anyway".
๐Ÿš€

How to Use Sherpa-ONNX (Beginner Quick Start Tutorial)

First time launching this application? Follow our beginner operational workflow:

1

Clone the Repository

Clone the sherpa-onnx GitHub repository to your local machine using git.

git clone https://github.com/k2-fsa/sherpa-onnx.git
2

Install Python Package

Install the python bindings via pip for quick offline transcription testing.

pip install sherpa-onnx
3

Download Pre-trained Models

Download the required ASR or TTS model files (like SenseVoice or VITS) from the Hugging Face space linked in the repo.

wget https://huggingface.co/.../model.onnx
4

Run Transcription

Execute the python script pointing to your audio file and model directory to get your offline transcript.

python3 -m sherpa_onnx.offline_asr --tokens=tokens.txt --model=model.onnx --audio=input.wav
๐Ÿ› ๏ธ

Troubleshooting & Fix Common Errors

If you encounter unexpected errors or installation failures, apply these verified diagnostic fixes:

โŒCUDA Out of Memory (OOM) Error

Root Cause: Your GPU VRAM is full because the AI model batch size or resolution is too high.

๐Ÿ’ก Solution Fix: Add '--lowvram' or '--medvram' argument to your launch command script, or lower the image/video batch size to 1.
โŒ'git', 'python' or 'ffmpeg' is not recognized as an internal command

Root Cause: The required software is installed but not added to your Windows Environment System PATH.

๐Ÿ’ก Solution Fix: Reinstall Python / Git and make sure to check the box 'Add Python.exe to PATH' during installation.
โŒTorch / PyTorch CUDA Version Mismatch

Root Cause: Installed PyTorch binary does not match your Nvidia GPU CUDA driver version.

๐Ÿ’ก Solution Fix: Run: pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
โŒPort 7860 or 8888 Already in Use

Root Cause: Another WebUI or Python background process is already running on the default local port.

๐Ÿ’ก Solution Fix: Close existing terminal windows, or add '--port 7861' parameter to change the default listening port.

๐Ÿ’ก Why Sherpa-ONNX is the Best Free Alternative to ElevenLabs and Cloud Whisper APIs

Bhai, agar aapko Bina internet ke fast captions generate karne hain ya local voice-over chahiye bina cloud subscription ke, toh yeh tool ekdum solid option hai.

If you are tired of expensive monthly subscription fees and privacy concerns, Sherpa-ONNX offers a completely free, open-source alternative. Running 100% locally on your computer (Windows, Mac, or Linux), it delivers high performance without export limits or cloud dependencies.

๐Ÿ“Š Comparison: Sherpa-ONNX vs Free Alternative to ElevenLabs and Cloud Whisper APIs

Feature / MetricSherpa-ONNX (Free Open-Source)Free Alternative to ElevenLabs and Cloud Whisper APIs (Paid)
Pricing Model100% Free Forever (โ‚น0)Paid Monthly Subscription
Data Privacy & Security100% Offline Local ComputerCloud Server Upload Required
System ControlFull Source Code & Custom ScriptsRestricted Closed Code
Community ExtensionsUnlimited GitHub PluginsLimited Official Marketplace
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๐Ÿ”— Source Code & Official Links

Finished reading the guide? You can inspect the source code or star the repository directly on GitHub below:

๐Ÿ”ฅ Related Open-Source Tools

Ajay K Meena
Written by Ajay K Meena
Cinematographer, Colorist & Director ยท Founder, Wedream Production

6+ years grading and shooting professionally in DaVinci Resolve โ€” from weddings and music videos to brand campaigns. Everything on this site is based on real production work, not recycled tutorials.