Notes:
Janus Recognition Toolkit (JRTk) has been used by the Interactive System Lab in many projects for speech recognition, such as BABEL. The Babel Program (IARPA) is developing agile and robust speech recognition technology that can be rapidly applied to any human language in order to provide effective search capability for analysts to efficiently process massive amounts of real-world recorded speech.
Wikipedia:
References:
- A chatbot for a dialogue-based second language learning system (2017)
- Deep Learning for Dialogue Systems (2017)
- Engineering General Intelligence, Part 1: A Path to Advanced AGI via Embodied Learning and Cognitive Synergy (2014)
- Engineering General Intelligence, Part 2: The CogPrime Architecture for Integrative, Embodied AGI (2014)
See also:
100 Best Deep Learning Videos | 100 Best GitHub: Deep Learning
Chitty-Chitty-Chat Bot: Deep Learning for Conversational AI.
R Yan – IJCAI, 2018 – ijcai.org
Conversational AI is of growing importance since it enables easy interaction interface between humans and computers. Due to its promising potential and alluring commercial values to serve as virtual assistants and/or social chatbots, major AI, NLP, and Search & …
Deep learning for dialogue systems
YN Chen, A Celikyilmaz, D Hakkani-Tur – Proceedings of the 27th …, 2018 – aclweb.org
Goal-oriented spoken dialogue systems have been the most prominent component in todays virtual personal assistants, which allow users to speak naturally in order to finish tasks more efficiently. The advancement of deep learning technologies has recently risen the …
Deep learning based chatbot models
R Csaky – arXiv preprint arXiv:1908.08835, 2019 – arxiv.org
A conversational agent (chatbot) is a piece of software that is able to communicate with humans using natural language. Modeling conversation is an important task in natural language processing and artificial intelligence. While chatbots can be used for various tasks …
Deep chit-chat: Deep learning for chatbots
W Wu, R Yan – Proceedings of the 42nd International ACM SIGIR …, 2019 – dl.acm.org
The tutorial is based on our long-term research on open domain conversation, rich hands-on experience on development of Microsoft XiaoIce, and our previous tutorials on EMNLP 2018 and the Web Conference 2019. It starts from a summary of recent achievement made by …
Deep Learning in Spoken and Text-Based Dialog Systems
A Celikyilmaz, L Deng, D Hakkani-Tür – Deep Learning in Natural …, 2018 – Springer
Last few decades have witnessed substantial breakthroughs on several areas of speech and language understanding research, specifically for building human to machine conversational dialog systems. Dialog systems, also known as interactive conversational …
Deep Learning for Chatbots
VA Bhagwat – 2018 – scholarworks.sjsu.edu
Abstract Natural Language Processing (NLP) requires modelling complex relationships between the semantics of the language. While traditional machine learning techniques are used for NLP, the models built for conversations, called chatbots, are unable to be truly …
Towards a deep learning question-answering specialized chatbot for objective structured clinical examinations
J El Zini, Y Rizk, M Awad… – 2019 International Joint …, 2019 – ieeexplore.ieee.org
Medical students undergo exams, called” Objective Structured Clinical Examinations”(OSCEs), to assess their medical competence in clinical tasks. In these OSCEs, a medical student interacts with a standardized patient, asking questions to …
KNADIA: Enterprise KNowledge assisted DIAlogue systems using deep learning
M Singh, P Agarwal, A Chaudhary… – 2018 IEEE 34th …, 2018 – ieeexplore.ieee.org
In this paper we present the design, architecture and implementation of KNADIA, a conversational dialogue system for intra-enterprise use, providing knowledge-assisted question answering and transactional assistance to employees of a large organization …
A deep reinforcement learning chatbot
IV Serban, C Sankar, M Germain, S Zhang… – arXiv preprint arXiv …, 2017 – arxiv.org
… We present MILABOT: a deep reinforcement learning chatbot developed by the Montreal … Dialogue systems and conversational agents – including chatbots, personal assistants and voice- control … We develop a new set of deep learning models for natural language retrieval and …
Deep learning for database mapping and asking clarification questions in dialogue systems
M Korpusik, J Glass – IEEE/ACM Transactions on Audio …, 2019 – ieeexplore.ieee.org
A dialogue system will often ask followup clarification questions when interacting with a user if the agent is unsure how to respond. In this new study, we explore deep reinforcement learning (RL) for asking followup questions when a user records a meal description, and the …
Developing FB Chatbot Based on Deep Learning Using RASA Framework for University Enquiries
Y Windiatmoko, AF Hidayatullah… – arXiv preprint arXiv …, 2020 – arxiv.org
Smart systems for Universities powered by Artificial Intelligence have been massively developed to help humans in various tasks. The chatbot concept is not something new in today society which is developing with recent technology. College students or candidates of …
An intelligent Chatbot using deep learning with Bidirectional RNN and attention model
M Dhyani, R Kumar – Materials Today: Proceedings, 2020 – Elsevier
This paper shows the modeling and performance in deep learning computation for an Assistant Conversational Agent (Chatbot). The utilization of Tensorflow software library, particularly Neural Machine Translation (NMT) model. Acquiring knowledge for modeling is …
A deep learning based chatbot for cultural heritage
G Sperlí – Proceedings of the 35th Annual ACM Symposium on …, 2020 – dl.acm.org
ABSTRACT In this paper we propose an entertainment Chatbot based on the sequence to sequence model according to the Enconder-Decoder framework based on GRU cells for supporting user’s cultural her- itage path. A preliminary evaluation about the efficiency of the proposed approach …
Deep learning for acoustic addressee detection in spoken dialogue systems
A Pugachev, O Akhtiamov, A Karpov… – Conference on Artificial …, 2017 – Springer
The addressee detection problem arises in real spoken dialogue systems (SDSs) which are supposed to distinguish the speech addressed to them from the speech addressed to real humans. In this work, several modalities were analyzed, and acoustic data has been chosen …
Ensemble-based deep reinforcement learning for chatbots
H Cuayáhuitl, D Lee, S Ryu, Y Cho, S Choi, S Indurthi… – Neurocomputing, 2019 – Elsevier
… We present a novel approach for chatbot training based on the reinforcement learning [2], unsupervised learning [3] and deep learning [4] paradigms. In contrast to other learning approaches for Deep Reinforcement Learning chatbots that rely on partially labelled dialogue …
An AI-Based Chatbot Using Deep Learning
M SENTHILKUMAR… – … Systems: Advances in …, 2019 – books.google.com
Chatbot is a vivid human-like contrivance which bounces chat. The main impartial of the chatbot is to authorization the customers and the machines to associate each other to altercation their chats. The way a machine can know human chats and how they response to …
A deep reinforcement learning chatbot (short version)
IV Serban, C Sankar, M Germain, S Zhang… – arXiv preprint arXiv …, 2018 – arxiv.org
… Conversational agents – including chatbots and personal assistants – are becoming increasingly ubiquitous … developed a new set of deep learning models for natural language retrieval and generation, including deep learning models … A Deep Reinforcement Learning Chatbot …
Contextual Chatbot for Healthcare Purposes (using Deep Learning)
P Kandpal, K Jasnani, R Raut… – 2020 Fourth World …, 2020 – ieeexplore.ieee.org
As the demand in Machine Learning & AI keeps growing, new technologies will keep coming in the market which will impact our day-to-day activities, and one such technology is Virtual Assistant Bots or simply Chatbots. Chatbots have evolved from being Menu/Button …
A Deep Learning Based Chatbot for Campus Psychological Therapy
J Yin, Z Chen, K Zhou, C Yu – arXiv preprint arXiv:1910.06707, 2019 – arxiv.org
In this paper, we propose Evebot, an innovative, sequence to sequence (Seq2seq) based, fully generative conversational system for the diagnosis of negative emotions and prevention of depression through positively suggestive responses. The system consists of …
Generative model chatbot for Human Resource using Deep Learning
SA Sheikh, V Tiwari, S Singhal – 2019 International Conference …, 2019 – ieeexplore.ieee.org
Human Resource is the working environment inside a business that is in charge of everything master related which unites selecting, checking, picking, verifying, on boarding, preparing, advancing, paying, and terminating delegates and freely utilized substances …
AI-Chatbot Using Deep Learning to Assist the Elderly
G Tascini – Systemics of Incompleteness and Quasi-Systems, 2019 – Springer
Abstract Recently Bot and Chatbot, both Artificial Intelligence software systems, have appeared online. These create a conversation between a virtual agent and the user. This paper describes an Artificial Intelligent Chatbot conversing with elderly persons, with age …
Sample efficient deep reinforcement learning for dialogue systems with large action spaces
G Weisz, P Budzianowski, PH Su… – IEEE/ACM Transactions …, 2018 – ieeexplore.ieee.org
… that this method beats the current state of the art in deep learning approaches for … A spoken dialogue system (SDS) aims to make the human-computer interaction more in- tuitive by … Spoken dialogue systems are complex as they have to solve many challenging problems at once …
Deep Learning Techniques for Implementation of Chatbots
SPR Karri, BS Kumar – 2020 International Conference on …, 2020 – ieeexplore.ieee.org
Chatbots are software programs that interact with clients using natural languages. The motto of the researchers was to know if chatbots can able to fool the clients that they were real humans. To develop a chatbot that can pass the Turing test, plenty of effort done with the …
A Deep Learning Methodology for Semantic Utterance Classification in Virtual Human Dialogue Systems
D Datta, V Brashers, J Owen, C White… – … Conference on Intelligent …, 2016 – Springer
This paper describes the development of a deep learning methodology for semantic utterance classification (SUC) for use in domain-specific dialogue systems. Semantic classifiers need to account for a variety of instances where the utterance for the semantic …
Deep learning based Text Emotion Recognition for Chatbot applications
M Karna, DS Juliet, RC Joy – 2020 4th International …, 2020 – ieeexplore.ieee.org
Emotions play a vital role in human interaction. We recognize emotion of a person from their speech, face gesture, body language and sign actions. Since humans use many text devices to make interactions these days, emotion extraction from the text has drawn a lot of …
A deep learning architecture for emotional aware chatbots
RH Grouls – 2020 – dspace.library.uu.nl
Chatbots cover a broad range of possible applications. Interacting with human emotions is a small but necessary subset of the skillset necessary for meaningful interaction. This paper explores strategies to create a chatbot that is able to adapt to the emotional cues during a …
Deep Learning-Based Multi-Chatbot Broker for Q&A Improvement of Video Tutoring Assistant
O Makhkamova, KH Lee, KH Do… – 2020 IEEE International …, 2020 – ieeexplore.ieee.org
Chatbot is software for conversations where the opponent is a program instead of a human. Marketing, business, education, healthcare, and other fields are using chatbots for the convenience of users. The functionality of the chatbot is like a virtual assistant for users to …
Deep Chit-Chat: Deep Learning for Chatbots
WWR Yan – Conference on Empirical Methods in Natural Language …, 2018 – ws.nju.edu.cn
Page 1. Deep Chit-Chat: Deep Learning for Chatbots Rui Yan, Assistant Professor Wangxuan Institute of Computer Technology (WICT), Peking University ruiyan@pku.edu.cn www.ruiyan.me Tutorial at EMNLP’18, WWW’19, SIGIR’19, together w/ Dr. Wei Wu from Micorsoft …
Deep reinforcement learning for multi-domain dialogue systems
H Cuayáhuitl, S Yu, A Williamson, J Carse – arXiv preprint arXiv …, 2016 – arxiv.org
… Recent work on deep learning applied to task-oriented conversational agents include the … RNN) for dialogue act prediction in a POMDP-based dialogue system, which focuses … RNN-based classifiers for predicting dialogue success in multi-domain dialogue systems, which can …
A general Chinese chatbot based on deep learning and its’ application for children with ASD
H Zhong, X Li, B Zhang… – International Journal of …, 2020 – researchportal.bath.ac.uk
Commercial chatbots such as Apple’s Siri, Microsoft’s XiaoIce, Amazon’s Alexa, Jingdong’s JIMI, and Alibaba’s Alime, have some great prospective in applications such as hosting programs, writing poetry, providing pre-sale consulting and after-sales service in E …
Invited Talks Invited Talk# 1 Deep Learning for NLG and Its Application For Chatbot System
M Le Nguyen – … 5th NAFOSTED Conference on Information and …, 2018 – ieeexplore.ieee.org
In this talk, we focus on showing the state-of-the-art works on natural language generation (NLG) using deep learning approaches. We will highlight existing works on NLG from the leading natural language processing conferences in 2018. We then present the application …
Chatbot using Deep Learning
SV Teja – drsrjournal.com
Intelligent Chatbot is a system which can interact with humans and answers questions on a certain domain. Today, the challenge is to build a system which will resemble human brain. Generally, the brain stores the memory in a decentralized manner across the brain with the …
Bbq-networks: Efficient exploration in deep reinforcement learning for task-oriented dialogue systems
ZC Lipton, X Li, J Gao, L Li, F Ahmed… – arXiv preprint arXiv …, 2016 – arxiv.org
… Task-Oriented dialogue systems In this paper, we consider goal-oriented dialogue agents, specifically one that aims to help … Figure 1: Components of a dialogue system … We are now ready to introduce BBQN, our algorithm for learning dialogue policies with deep learning models …
Expression Tracking with OpenCV Deep Learning for a Development of Emotionally Aware Chatbots
KALR Carranza, J Manalili, NT Bugtai… – 2019 7th …, 2019 – ieeexplore.ieee.org
Affective computing explores the development of systems and devices that can perceive, translate, process, and reproduce human emotion. It is an interdisciplinary field which includes computer science, psychology and cognitive science. An inspiration for the …
Smart Ubiquitous Chatbot for COVID-19 Assistance with Deep learning Sentiment Analysis Model during and after quarantine
N Ouerhani, A Maalel, HB Ghézala, S Chouri – 2020 – researchsquare.com
The huge number of deaths caused by the novel pandemic COVID-19, which can affect anyone of any sex, age and socio-demographic status in the world, presents a serious threat for humanity and society. At this point, there are two types of citizens, those oblivious of this …
Developing Chatbot with Deep Learning Techniques for Negotiation Course
MY Chang, JP Hwang – 2019 8th International Congress on …, 2019 – ieeexplore.ieee.org
this research combines the artificial intelligence technique RNN/LSTM to develop a dialogue system, which mainly used in the bargaining unit of a negotiation course. The chatbot was applied in the dialogue of student drills in bargaining situations and investigates the …
COVID-19 Chat Bot by using Deep Learning
SH Lee, JS Jeong, YJ Kim, H Kwon… – Proceedings of the …, 2020 – koreascience.or.kr
? ????? ?? ??? ?? ?? ???? ??? ???? ????? ???? ???? Seq2seq ??? ??? ???? ??? ???? … (34141) Korea Institute of Science and Technology Information, 245, Daehak-ro, Yuseong-gu, Daejeon TEL 042)869-1004 Copyright …
Developing Dialog Manager in Chatbots via Hybrid Deep Learning Architectures
B Ali, V Ravi – Intelligent Data Engineering and Analytics – Springer
Dialog Manager has played a great role in conversational AI so much, so that it is also called the heart of a dialog system. It has been employed in task-oriented Chatbot to learn the context of a conversation and come up with some representation which helps in executing …
SimpleDS: A Simple Deep Reinforcement Learning Dialogue System
H Cuayáhuitl – Dialogues with social robots, 2017 – Springer
… In contrast to previous reinforcement learning dialogue systems, SimpleDS selects dialogue actions directly from raw (noisy) text of … training parameters and reward functions; (b) extend or improve the abilities of the proposed dialogue system; (c) train deep learning agents in …
Chatbots with Personality Using Deep Learning
S Gaikwad – 2019 – scholarworks.sjsu.edu
Abstract Natural Language Processing (NLP) requires the computational modelling of the complex relationships of the syntax and semantics of a language. While traditional machine learning methods are used to solve NLP problems, they cannot imitate the human ability for …
Deep Learning based Situated Goal-oriented Dialogue Systems.
D Hakkani-Tür – INTERSPEECH, 2018 – isca-speech.org
Interacting with machines in natural language has been a holy grail since the beginning of computers. Given the difficulty of understanding natural language, only in the past couple of decades, we started seeing real user applications for targeted/limited domains. More …
A General Chinese Chatbot based on Deep Learning and Its’ Application for Children with ASD
X LI, H ZHONG, B ZHANG, J ZHANG – academia.edu
Microsoft’s XiaoIce, Amazon’s Alexa, Jingdong’s JIMI, and Alibaba’s Alime, have some great prospective in applications such as hosting programs, writing poetry, providing pre-sale consulting and after-sales service in E-commerce, and providing virtual shopping guidance …
Sentiment Analysis and Deep Learning Based Chatbot for User Feedback
S Sankar – Intelligent Communication Technologies and Virtual …, 2019 – Springer
Recently, the conversational agents like Chatbots are widely employed for achieving a better Human-Computer Interaction (HCI). In this paper, a retrieval based chatbot is designed using Natural Language Processing (NLP) techniques and a Multilayer …
Intelligent Chatbot using Deep Learning
V Rus – 2018 – researchgate.net
Abstract Dialogue Generation or Intelligent Conversational Agent development using Arti icial Intelligence or Machine Learning technique is an interesting problem in the ield of Natural LanguageProcessing. Inmanyresearchanddevelopmentprojects, theyareusingArti …
Deep reinforcement learning for chatbots using clustered actions and human-likeness rewards
H Cuayáhuitl, D Lee, S Ryu, S Choi… – … Joint Conference on …, 2019 – ieeexplore.ieee.org
… novel approach based on the reinforcement learning [2], unsupervised learning [3] and deep learning [4] paradigms … fact that task-oriented dialogue systems use finite action sets, while chatbot systems use … So far there is a preference for policy search methods for chatbots, but it …
Deep learning for spoken dialogue systems: application to nutrition
MB Korpusik – 2019 – dspace.mit.edu
Personal digital assistants such as Siri, Cortana, and Alexa must translate a user’s natural language query into a semantic representation that the back-end can then use to retrieve information from relevant data sources. For example, answering a user’s question about the …
The use of Grid technologies and corpus linguistics in deep learning of dialog system
DS Kurushin, OV Soboleva, AI Sholomova… – ???????????? …, 2020 – elibrary.ru
Although it is now possible to build real-time spoken dialogue systems for a wide variety of applications, designing the dialogue strategy of such systems involves a number of nontrivial design choices. These choices can seriously impact system performance, and …
ARTIFICIAL INTELLIGENCE BASED CHATBOT FOR HUMAN RESOURCE USING DEEP LEARNING A DISSERTATION
SA Sheikh – 2019 – researchgate.net
Human Resource is the workplace inside a business that is responsible for everything expert related which consolidates enrolling, checking, picking, securing, on boarding, getting ready, progressing, paying, and firing delegates and independently employed …
Intelligent Dialogue System Based on Deep Learning Technology
I Sidenko – pdfs.semanticscholar.org
Recent advances in machine learning has contributed to the rebirth of the chat-bot. Lately we have seen a rise in chat-bot technology being made available on the web and on mobile devices, and recent reports states that 57% of companies have implemented or are planning …
Deep learning for automatic dialogue system
W Liu – 2018 – dr.ntu.edu.sg
Dialogue systems, also known as interactive conversations agents, virtual agents and sometimes chatterbots has been widely applied into daily life from entertainment to automation customer services such as personalised medical service and online shopping …
Scaling up deep reinforcement learning for multi-domain dialogue systems
H Cuayáhuitl, S Yu, A Williamson… – 2017 International Joint …, 2017 – ieeexplore.ieee.org
… To our knowledge, we report one of the first multi-domain dialogue system using deep reinforcement learning. Future work includes applying neural-based dialogue systems to larger sets of domains, to language generation using a divide-and-conquer approach [28], to multi …
Deep Reinforcement Learning for Dialogue Systems with Dynamic User Goals
G Chandler – 2020 – scholarcommons.scu.edu
… Some of these areas include natural language understanding and generation, deep learning, reinforcement learning, expert systems, 6 … one of the first “chat bots” … After forming an understanding of this current dialogue system, we will discuss some of the implications …
Deep reinforcement learning in dialog systems
D Väth – 2018 – elib.uni-stuttgart.de
… driven SDS. Task-driven dialog systems try to assist a user achieving a certain goal. For example, a restaurant search system might help the user to identify … Figure 1: Schematic of a modular dialog system. Adapted from Williams et al. (2016) … called deep learning. 13 Page 24 …
Customer Centric Artificial Intelligence-Using Text and Sentiment Analysis & Deep Neural Network Learning to make Chatbots Reply in a more Customer …
A Schreuder, A Schreuder, J van Wyk – 2017 – samra.co.za
… foundational focus of the paper is the Artificial Intelligence and specifically deep learning neural networks … The Chatbot will thus learn what types of responses are Customer Centric. From this basic research, Chatbots can be extended to generate lexical output by implementing …