深度学习聊天机器人资源集合 Awesome chatbot resource list
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Contributions Welcome

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




Framework tensorflow

A toy chatbot powered by deep learning and trained on data from Reddit.

> Hi, how are you?
 I'm not the only one here that's having fun with you, it's all me.
> Who else is with you?
 Haha. I'm not the one who made the comment. I'm the one who said that and didn't think that much of anything. 
> Oh, I see. So what's new?
 Nothing. I just thought it was a bit of an overreaction. It's been a while since I've read it. 
> It's all good
 It's all good. It's one of those things that makes me smile :)
> That's great. This is actually my demo chat, so it's nice that you're keeping things positive!
 Thank you :) 


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...


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					→ hello
how old are you ?			→ twenty .
i am lonely					→ i am not
nice						→ 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 .

machine translation model

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 .


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!


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。 chatbot-zh-torch7


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


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


Framework: python


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




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.


    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 .  






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

Cornell Movie-Dialogs Corpus

~ 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。



Some English QA Material

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。


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。






Github fork