Displaying 1 to 5 from 5 results

cakechat - CakeChat: Emotional Generative Dialog System

  •    Python

It is written in Theano and Lasagne. It uses end-to-end trained embeddings of 5 different emotions to generate responses conditioned by a given emotion. The code is flexible and allows to condition a response by an arbitrary categorical variable defined for some samples in the training data. With CakeChat you can, for example, train your own persona-based neural conversational model[5] or create an emotional chatting machine without external memory[4].

TC-Bot - User Simulation for Task-Completion Dialogues

  •    OpenEdge

An implementation of the End-to-End Task-Completion Neural Dialogue Systems and A User Simulator for Task-Completion Dialogues. This document describes how to run the simulation and different dialogue agents (rule-based, command line, reinforcement learning). More instructions to plug in your customized agents or user simulators are in the Recipe section of the paper.

ConvAI-baseline - ConvAI baseline solution

  •    Python

Python packages will be installed by setup.sh script. Setup will download docker images, models and data files, so you have no need to download any of that by yourself.




convai-bot-1337 - Skill-based Conversational Agent for NIPS Conversational Intelligence Challenge 2017

  •    Python

Skill-based Conversational Agent that took 1st place at 2017 NIPS Conversational Intelligence Challenge (http://convai.io). We still update our Conversational Agent and the latest version could be found in master branch.






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