k2-fsa/sherpa-ncnn

Health v2 · maintenance only

Adoption not part of the score

1779 stars · 218 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A C++ library for real-time offline speech recognition, text-to-speech, and voice activity detection built on the ncnn inference framework with next-gen Kaldi models. It runs entirely on-device without Internet access and provides APIs for C++, C, Python, Go, C#, Kotlin, Swift, and JavaScript across mobile, desktop, and embedded platforms.

Use cases

• run offline speech-to-text on android or ios without internet
• real-time microphone transcription on raspberry pi
• add voice activity detection to an embedded device
• on-device text to speech with vits models
• build a wasm browser-based speech recognizer
• streaming asr on risc-v boards like visionfive2

When to choose

• you need fully offline, low-latency speech recognition on mobile or embedded hardware
• you cannot depend on PyTorch or cloud services and want lightweight ncnn inference
• you need bindings across many languages and platforms including ARM and RISC-V

When to avoid

• you need GPU-accelerated server-scale ASR with the latest large models
• you want PyTorch-based tooling or training pipelines (use icefall/sherpa-onnx instead)
• you need extensive prebuilt model variety beyond the provided ncnn-exported models

Facets

library · maturity active

speech-recognition tts audio-processing sdk speech-processing embedded-systems cross-platform windows cpp python wasm embedded cross-platform offline-asr ncnn voice-activity-detection streaming-recognition raspberry-pi risc-v on-device-inference kaldi natural-language-processing android ios linux macos

Member repositories

For agents

markdown · JSON · MCP: product_card(name="k2-fsa/sherpa-ncnn")