An open source library for deep learning end-to-end dialog systems and chatbots.

Snips Python library to extract meaning from text

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

building a chinese dialogue system based on the newest version of rasa(基于最新版本rasa搭建的对话系统)

A practical and feature-rich paraphrasing framework to augment human intents in text form to build robust NLU models for conversational engines. Created by Prithiviraj Damodaran. Open to pull requests and other forms of collaboration.

Pytorch implementation of JointBERT: "BERT for Joint Intent Classification and Slot Filling"

On-device Speech-to-Intent engine powered by deep learning

[ACL 2021] Learning Dense Representations of Phrases at Scale; EMNLP'2021: Phrase Retrieval Learns Passage Retrieval, Too https://arxiv.org/abs/2012.12624

A TensorFlow implementation of Recurrent Neural Networks for Sequence Classification and Sequence Labeling

slot filling, intent detection, joint training, ATIS & SNIPS datasets, the Facebook’s multilingual dataset, MIT corpus, E-commerce Shopping Assistant (ECSA) dataset, CoNLL2003 NER, ELMo, BERT, XLNet

[EMNLP 2020] OpenUE: An Open Toolkit of Universal Extraction from Text

Slot-Gated Modeling for Joint Slot Filling and Intent Prediction

Tensorflow implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling" (https://arxiv.org/abs/1609.01454)

[NAACL 2021] This is the code for our paper `Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach'.

Pytorch implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling" (https://arxiv.org/abs/1609.01454)

中文自然语言的实体抽取和意图识别（Natural Language Understanding），可选Bi-LSTM + CRF 或者 IDCNN + CRF

attention based joint model for intent detection and slot filling

基于pytorch的中文意图识别和槽位填充

Open source code for EMNLP-19 Paper "A Stack-Propagation Framework with Token-Level Intent Detection for Spoken Language Understanding".

Joint Slot Filling and Intent Detection via Capsule Neural Networks (ACL'19) https://arxiv.org/abs/1812.09471