精品--深度学习聊天机器人资源集合 Awesome chatbot resource list.zip

Know a resource that isn't listed below? Feel free to create a new [pull request](https://github.com/fateleak/awesome-chatbot-list/pulls), or open an [issue](https://github.com/fateleak/awesome-chatbot-list/issues/new).Seq2seq/chatbot/聊天机器人相关资源收集列表。 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。 ___ ## Codes #### [chatbot-rnn](https://github.com/pender/chatbot-rnn) 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 :) ``` #### [DeepQA](https://github.com/Conchylicultor/DeepQA) 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... #### [tf_seq2seq_chatbot](https://github.com/nicolas-ivanov/tf_seq2seq_chatbot) 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](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/models/rnn/translate) 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。  #### [Neural-Dialogue-Generation](https://github.com/jiweil/Neural-Dialogue-Generation) 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 . #### [neuralconvo](https://github.com/macournoyer/neuralconvo) 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! #### [chatbot-zh-torch7](https://github.com/fateleak/chatbot-zh-torch7) 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。  #### [Seq2seq_Chatbot_QA](https://github.com/qhduan/Seq2Seq_Chatbot_QA) 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 #### [ChatterBot](https://github.com/gunthercox/ChatterBot) 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? #### [farizrahman4u/seq2seq](https://github.com/farizrahman4u/seq2seq) #### [nicolas-ivanov/debug_seq2seq](https://github.com/nicolas-ivanov/debug_seq2seq) #### [codekansas/keras-language-modeling](https://github.com/codekansas/keras-language-modeling) Framework: keras 这几个都是seq2seq的实现，但是在Chatbot上面还没有好的demo result。 #### [oswaldoludwig/Seq2seq-Chatbot-for-Keras](https://github.com/oswaldoludwig/Seq2seq-Chatbot-for-Keras) 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 . ### [pydial](http://www.camdial.org/pydial/) 一个多领域多轮会话的开发框架  [paper](http://www.aclweb.org/anthology/P17-4013) - 剑桥的开源DS [PyDial](http://www.camdial.org/pydial/) - 一个开源的DS [deepmipt/DeepPavlov](https://github.com/deepmipt/DeepPavlov) - 一个商业但开源的DS [Rasa Core](https://rasa.com/) - 比较简单的机器人[ChatterBot](https://github.com/gunthercox/ChatterBot) - 一个开源的QA系统，里面那个论文列表不错 [castorini/BuboQA](https://github.com/castorini/BuboQA) - AIML的公司 [pandorabots](https://home.pandorabots.com/en/) ### ## Corpus #### [AlJohri/OpenSubtitles](https://github.com/AlJohri/OpenSubtitles) Get a lot of raw movie subtitles (~1.2Gb) #### [Cornell Movie-Dialogs Corpus](http://www.cs.cornell.edu/~cristian/Cornell_Movie-Dialogs_Corpus.html) ~ 40Mb after clearing out the technical data. #### [dgk_lost_conv](https://github.com/fateleak/dgk_lost_conv) [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。 #### [Some English QA Material](https://github.com/karthikncode/nlp-datasets) 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�