Hugging Face, ModelScope, and k2-fsa.github.io (specifically the k2-fsa/sherpa-onnx project) represent different approaches to the machine learning ecosystem。

Hugging Face and ModelScope host everything. k2-fsa and Sherpa only do Speech.

k2-fsa and Sherpa are highly specialized tools focused on speech recognition (ASR) and synthesis (TTS)

 

Sherpa (often referred to as sherpa-onnx or sherpa-ncnn) is a lightweight speech-to-text (ASR) and text-to-speech (TTS) engine. Best for: Deploying speech models on edge devices (Android, iOS, WebAssembly, ARM boards) or high-performance servers, prioritizing low latency and CPU efficiency.

Table of Contents

These four entities represent two different categories: Model Ecosystems (Hugging Face & ModelScope) and Speech Recognition Frameworks (Kaldi & k2-fsa).

 

Hugging Face（Global AI model platform）

The Global Industry Standard。It supports NLP, computer vision, audio, and multimodal models via transformers and diffusers libraries.

 

https://huggingface.co/models

 

https://huggingface.co/FunAudioLLM/SenseVoiceSmall

 

ModelScope(The Alibaba/Chinese AI Industrial model platform) 

ModelScope is an AI model hub led by Alibaba DAMO Academy. It provides pre-trained models, pipelines, and deployment tools, especially strong in Chinese language and speech technologies.ModelScope is often described as the "Chinese Hugging Face."

 

https://modelscope.cn/search?search=sherpa%20onnx

 

specialized tools focused on speech recognition (ASR) and synthesis (TTS)

 

Kaldi: Speech Toolkit

The "grandfather" of modern speech recognition. It is a C++ based toolkit developed primarily by Dan Povey.

demo

KaldiRecognizer

https://github.com/rhasspy/wyoming-faster-whisper/blob/main/wyoming_faster_whisper/__main__.py

k2-fsa (Next-Gen Kaldi)

 Speech Toolkit.The Modern Successor

What it is: Often called "Next-gen Kaldi." It is a complete rewrite of Kaldi’s core concepts to make them natively compatible with PyTorch.

Key Repositories:

Icefall: Where the actual training recipes for speech models (like Zipformer) live.

k2: The core library for differentiable FSTs.the old version of the tool you used before k2-fsa existed.

 

 download Silero VAD ONNX model

# https://k2-fsa.github.io/sherpa/onnx/sense-voice/pretrained.html#sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17
wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/silero_vad.onnx

 

download url:https://k2-fsa.github.io/sherpa/onnx/vad/silero-vad.html#download-models-files

 

Sherpa(The Real-Time Speech Deployment Tool)

The deployment engine (CPU/GPU, Android, iOS, WebAssembly).It uses models trained in the k2-fsa ecosystem.

 

How they all fit together

1.k2-fsa is the tool you use to build a high-performance speech model.

silero-vad model download

https://k2-fsa.github.io/sherpa/onnx/vad/silero-vad.html#download-models-files

 

Once you've trained that model using k2-fsa, you might upload it to Hugging Face or ModelScope so others can download it easily.

Hugging Face hosts models from both ModelScope and k2-fsa/Sherpa, serving as a distribution point for them. 

 

 

Layer Relationship

Model Hosting & Distribution
   ├── ModelScope
   └── Hugging Face

Inference / Runtime Framework
   └── k2-fsa / sherpa

 

 

 

Comments

Be the first to post a comment

Post a comment