Seq2seq/chatbot/聊天机器人相关资源收集列表。 Know a resource that isn't listed below? Feel free to create a new , or open an .

在原来的chatbot-links的基础上，添加了一些更多的中文资源而组建的一个List，主要用于个人收集。感兴趣，一起建设完善的资源列表，方便萌新入门，请发送PR或Issue添加更多资源，各层面不限，欢迎添加自己的作品。

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Codes

Framework: Tensorflow Demo result:

Hi			            	→ Hi.What is your name ?			→ Laura.What does that mean ?		→ I dunno.How old are you ?			→ thirty-five.Who is Laura ?				→ My brother.Say 'goodbye'				→ Alright.Two plus two				→ manny...复制代码

Framework: Tensorflow

No answering randomisation is implemented in this code, so the models answers with the same phrase way each time: 未实现回答的是随机化，仅对模型的末尾加入了稀疏层。

hello baby					→ hellohow old are you ?			→ twenty .i am lonely					→ i am notnice						→ you ' re not going to be okay .so rude						→ i ' m sorry .are you a robot or human?	→ no .are you better than siri?	→ yes .复制代码

Framework: Tensorflow

Google Official seq2seq implementation, attention included. Originlly for translation, can be used as Q/A; Google官方的seq2seq实现，采用了注意力机制(Luong et al., 2015)，原本用于语言翻译，也适用于简单Q/A。

Framework: Torch 6.x Source code for a bunch of super nice articles by Jiwei Li - one of my favorite researches in the domain of neural conversational systems. Worth checking out.

tell me ... how long have you had this falling sickness ?       → a few months, I guess .so i had the doctors test sammy ’s response to conditioning .   → so he took the pills .what are you going to do ?                                      → i ’m going to get you a new car .they fear your power your intellect .                           → i ’m not afraid of your power .复制代码

Framework: Torch 7

最早的对《A Neural Conversational Model》的实现之一，当时给的Demo效果非常有意思。

Hello?					→ Hi.How are you?			→ I'm fine.What's your name?		→ It's hard to describe.How so?					→ I'm not sure.What color is the sky?	→ It's blue.What is your job?		→ It's not that i'm a fucking werewolf!复制代码

Framework: Torch 7

从neuralconvo修改而来的，当时应该是第一个中文的RNN based chatbot DEMO。

Framework: Tensorflow 一个中文的Demo，说明比较详细，推荐。

result:

你到哪里去        →你不是说你不是我的你喜欢我吗？      →我喜欢你你吃了吗？        →我还没吃饭呢你喜欢喝酒吗？     →我不知道你说话没有逻辑啊   →没有复制代码

Framework: python

看上去比较完整的一个项目，安装简单，说明比较完善，有提供训练的材料，英文为主。

Good morning! How are you doing?   →I am doing very well, thank you for asking.You're welcome.                    →Do you like hats?复制代码

Framework: keras

这几个都是seq2seq的实现，但是在Chatbot上面还没有好的demo result。

A new generative chatbot whose training converges in few epochs, including a model pre-trained on a small but consistent dataset collected from dialogues of English courses online.

这个采用了生成模型的方式，待补充。

user:  Hello! How are you?computer:  i am fine , ok , well , thank you  .      user:  What's your name?computer:  janet .       user:  What do you like to do now?computer:  let me think a minute .       user:  I want to chat about computer science.computer:  i am glad to hear there .       user:  Are you a real girl or a computer program?computer:  i am self employed . i would love to be well .       user:  Why don't you look for a job?computer:  i do not know . i am the bank .       user:  So, you don't need a job!computer:  no . i have to make a lot of money .  复制代码

Corpus

Get a lot of raw movie subtitles (~1.2Gb)

~ 40Mb after clearing out the technical data.

[中文]语料。大部分为由字幕生成的材料，少量其它对话(如以前的小黄鸡的材料，我从一位网友朋友那里要过来了，感谢他)。 其中results/xiaohuangji50w_fenciA.conv.zip为上面chatbot-zh-torch7的演示的训练材料。

[原射手网的打包字幕合集17G]

现已关闭的射手网有一个所有字幕的合集包，感兴趣的同学需要自行网上搜索下载。

这是他人收集的自然语言处理相关数据集，主要包含Question Answering，Dialogue Systems， Goal-Oriented Dialogue Systems三部分，都是英文文本。可以使用机器翻译为中文，供中文对话使用。

TODO

dgk_lost_conv中字幕生成的材料的问题是质量较差，这是因为字幕文件中包含了很多的旁白，或者单人连续说话的情况，而这些在处理的时候都没有剔除掉。希望有同学能够找到方法。 或者 从微博、QQ群、微信群等地方挖掘更多的1v1的对话材料。

Papers

贡献列表

Refs：

为了方便中文用户中对chatbot/NLP/DeepLearning感兴趣的朋友们互相交流，建了一个QQ群，欢迎您加入讨论：