Introduction

sherpa is the deployment framework of the Next-gen Kaldi project.

sherpa does only one thing, using a pre-trained model to transcribe speech. If you are interested in how to train your own model or fine tune a pre-trained model, please refer to icefall.

At present, sherpa has the following sub-projects:

The differences are compared below:

k2-fsa/sherpa

k2-fsa/sherpa-onnx

k2-fsa/sherpa-ncnn

Installation difficulty

hard

easy

easy

NN lib

PyTorch

onnxruntime

ncnn

CPU Support

x86, x86_64
x86, x86_64,
arm32, arm64
x86, x86_64,
arm32, arm64,
**RISC-V**

GPU Support
Yes
(with CUDA for NVIDIA GPUs)

Yes
Yes
(with Vulkan for ARM GPUs)

OS Support
Linux, Windows,
macOS
Linux, Windows,
macOS, iOS,
Android
Linux, Windows,
macOS, iOS,
Android

Support batch_size > 1

Yes

Yes

No

Provided APIs

C++, Python
C, C++, Python,
C#, Java, Kotlin,
Swift
C, C++, Python,
C#, Kotlin,
Swift

Model types
streaming,
non-streaming
streaming,
non-streaming

streaming only

We also support Triton. Please see Triton.