syw2014

MockingBird

🚀AI拟声: 5秒内克隆您的声音并生成任意语音内容 Clone a voice in 5 seconds to generate arbitrary speech in real-time

Dialogue

AlgoNotes

【浅梦学习笔记】文章汇总:包含 排序&CXR预估，召回匹配，用户画像&特征工程，推荐搜索综合 计算广告，大数据，图算法，NLP&CV，求职面试 等内容

poetry

汉语现代诗歌语料库整理，3489诗人，81.7K诗歌，15.43M字。持续扩充...

Chatbot_CN

基于金融-司法领域(兼有闲聊性质)的聊天机器人，其中的主要模块有信息抽取、NLU、NLG、知识图谱等，并且利用Django整合了前端展示,目前已经封装了nlp和kg的restful接口

lightseq

LightSeq: A High Performance Library for Sequence Processing and Generation

pretrained-models

Open Language Pre-trained Model Zoo

ML-examples

Arm Machine Learning tutorials and examples

effective_transformer

Running BERT without Padding

UER-py

Open Source Pre-training Model Framework in PyTorch & Pre-trained Model Zoo

Dev-Cpp

A fast, portable, simple, and free C/C++ IDE

spokestack-python

Spokestack is a library that allows a user to easily incorporate a voice interface into any Python application with a focus on embedded systems.

wenet

Production First and Production Ready End-to-End Speech Recognition Toolkit

lac

百度NLP：分词，词性标注，命名实体识别，词重要性

Chatbot_Retrieval

基于检索的任务型多轮对话

ChineseNLP

Datasets, SOTA results of every fields of Chinese NLP

nlp_paper_study

该仓库主要记录 NLP 算法工程师相关的顶会论文研读笔记

modern-cpp-tutorial

📚 Modern C++ Tutorial: C++11/14/17/20 On the Fly | https://changkun.de/modern-cpp/

CMakeTutorial

CMake中文实战教程

Principle-of-Web-Search

北京邮电大学“网络搜索原理”课程资料(2019)

ConvLab-2

ConvLab-2: An Open-Source Toolkit for Building, Evaluating, and Diagnosing Dialogue Systems

unit-uskit

unit-uskit

awesome-cpp

A curated list of awesome C++ (or C) frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff.

Reflection_Summary

算法理论基础知识应知应会

Silent-Face-Anti-Spoofing

静默活体检测（Silent-Face-Anti-Spoofing）

efaqa-corpus-zh

❤️Emotional First Aid Dataset, 心理咨询问答、聊天机器人语料库

Medical_NLP

Medical NLP Competition, dataset, large models, paper

gruvbox

Retro groove color scheme for Vim

fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

NLPGNN

1. Use BERT, ALBERT and GPT2 as tensorflow2.0's layer. 2. Implement GCN, GAN, GIN and GraphSAGE based on message passing.