[HTML][HTML] A review of ai-driven conversational chatbots implementation methodologies and challenges (1999–2022)
A conversational chatbot or dialogue system is a computer program designed to simulate
conversation with human users, especially over the Internet. These chatbots can be …
conversation with human users, especially over the Internet. These chatbots can be …
A survey on empathetic dialogue systems
Dialogue systems have achieved growing success in many areas thanks to the rapid
advances of machine learning techniques. In the quest for generating more human-like …
advances of machine learning techniques. In the quest for generating more human-like …
Deep reinforcement learning for dialogue generation
Recent neural models of dialogue generation offer great promise for generating responses
for conversational agents, but tend to be shortsighted, predicting utterances one at a time …
for conversational agents, but tend to be shortsighted, predicting utterances one at a time …
[HTML][HTML] Survey on evaluation methods for dialogue systems
In this paper, we survey the methods and concepts developed for the evaluation of dialogue
systems. Evaluation, in and of itself, is a crucial part during the development process. Often …
systems. Evaluation, in and of itself, is a crucial part during the development process. Often …
Deal or no deal? end-to-end learning for negotiation dialogues
Much of human dialogue occurs in semi-cooperative settings, where agents with different
goals attempt to agree on common decisions. Negotiations require complex communication …
goals attempt to agree on common decisions. Negotiations require complex communication …
Transfer learning
SJ Pan - Learning, 2020 - api.taylorfrancis.com
Supervised machine learning techniques have already been widely studied and applied to
various real-world applications. However, most existing supervised algorithms work well …
various real-world applications. However, most existing supervised algorithms work well …
Sample-efficient actor-critic reinforcement learning with supervised data for dialogue management
Deep reinforcement learning (RL) methods have significant potential for dialogue policy
optimisation. However, they suffer from a poor performance in the early stages of learning …
optimisation. However, they suffer from a poor performance in the early stages of learning …
Robust dialog state tracking using delexicalised recurrent neural networks and unsupervised adaptation
M Henderson, B Thomson… - 2014 IEEE Spoken …, 2014 - ieeexplore.ieee.org
Tracking the user's intention throughout the course of a dialog, called dialog state tracking, is
an important component of any dialog system. Most existing spoken dialog systems are …
an important component of any dialog system. Most existing spoken dialog systems are …
Artificial conversations for customer service chatter bots: Architecture, algorithms, and evaluation metrics
C Chakrabarti, GF Luger - Expert Systems with Applications, 2015 - Elsevier
Chatter bots are software programs that engage in artificial conversations through a text-
based input medium. They are extensively deployed in customer service applications …
based input medium. They are extensively deployed in customer service applications …
Is spoken language all-or-nothing? Implications for future speech-based human-machine interaction
RK Moore - Dialogues with Social Robots: Enablements, Analyses …, 2017 - Springer
Recent years have seen significant market penetration for voice-based personal assistants
such as Apple's Siri. However, despite this success, user take-up is frustratingly low. This …
such as Apple's Siri. However, despite this success, user take-up is frustratingly low. This …