技能目录

为 AI Agent 发现可复用技能。

按任务搜索真实的 GitHub 技能,并在使用前查看 Stars、信任、审计、分类和安装路径。

每个推荐都保留与其仓库、审计和安装路径的明确关联。

搜索结果: multilingual-nlp

英文目录

VoxCPM2: Tokenizer-Free TTS for Multilingual Speech Generation, Creative Voice Design, and True-to-Life Cloning

31K
Stars
87/100
信任
分类: media-automation审计

Tongyi Deep Research, the Leading Open-source Deep Research Agent

20K
Stars
81/100
信任
分类: research审计

Multilingual speech understanding: ASR + emotion recognition + audio event detection. 50+ languages, 15x faster than Whisper, non-autoregressive.

8.6K
Stars
77/100
信任
分类: media-automation审计

Lightning-Fast, On-Device, Multilingual TTS — running natively via ONNX.

12K
Stars
81/100
信任
分类: media-automation审计

Gradio WebUI for creators and developers, featuring key TTS (Edge-TTS, kokoro) and zero-shot Voice Cloning (E2 & F5-TTS, CosyVoice), with Whisper audio processing, YouTube download, Demucs vocal isolation, and multilingual translation.

12K
Stars
87/100
信任
分类: media-automation审计

💫 Industrial-strength Natural Language Processing (NLP) in Python

34K
Stars
81/100
信任
分类: ml-automation审计

An open-source framework for detecting, redacting, masking, and anonymizing sensitive data (PII) across text, images, and structured data. Supports NLP, pattern matching, and customizable pipelines.

9.8K
Stars
86/100
信任
分类: legal-compliance审计

An open-source framework for detecting, redacting, masking, and anonymizing sensitive data (PII) across text, images, and structured data. Supports NLP, pattern matching, and customizable pipelines.

9.4K
Stars
86/100
信任
分类: legal-compliance审计

Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages

7.8K
Stars
77/100
信任
分类: ml-automation审计

快速上手AI理论及应用实战:基础知识、Transformer、NLP、ML、DL、竞赛。含大量注释及数据集,力求每一位能看懂并复现。

3.5K
Stars
80/100
信任
分类: ml-automation审计

An agent skill that scans web projects for common AI-generated design patterns and suggests or applies fixes to remove them.

786
Stars
84/100
信任
分类: design-creative审计

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现,也是作为一个算法工程师必会的理论基础知识。

18K
Stars
76/100
信任
分类: ml-automation审计