Intent, Named Entity & Dialog Systems 2017


Notes:

A named entity is a real-world object, such as persons, locations, organizations, products, etc., that can be denoted with a proper name.

  • Belief tracking
  • Intent detection
  • Proof tree
  • Slot filling

Resources:

Wikipedia:

References:

See also:

100 Best GitHub: Named-Entity RecognitionBDI (Belief-Desire-Intention) & Dialog Systems | Intent, Dialog Act & Dialog Systems 2017


Spoken language understanding for a nutrition dialogue system
M Korpusik, J Glass – IEEE/ACM Transactions on Audio …, 2017 – ieeexplore.ieee.org
… language understanding (SLU) in dialogue systems (ie, deter- mining user intent and slot … We also examine the closely related task of named entity recognition and classification (NERC). Fi- nally, we present work in spoken dialogue systems (SDS) and distributional semantics …

Frames: A corpus for adding memory to goal-oriented dialogue systems
LE Asri, H Schulz, S Sharma, J Zumer, J Harris… – arXiv preprint arXiv …, 2017 – arxiv.org
… An intent indicates whether or not the user wants to book a package, whereas an … To imitate this behaviour, a dialogue system would need to reason over the database and decide … part operates on character trigrams and is based on the robust named entity recognition model …

Generative encoder-decoder models for task-oriented spoken dialog systems with chatting capability
T Zhao, A Lu, K Lee, M Eskenazi – arXiv preprint arXiv:1706.08476, 2017 – arxiv.org
… the user utterances into semantic frames that contain domain-specific slots and intents using spoken … Users were able to talk to a web interface to the dialog systems via speech … Lastly, a hybrid named entity recognizer (NER) was trained using Conditional Random Field (CRF …

Just ASK: Building an Architecture for Extensible Self-Service Spoken Language Understanding
A Kumar, A Gupta, J Chan, S Tucker… – arXiv preprint arXiv …, 2017 – arxiv.org
… [22] Guillaume Lample, Miguel Ballesteros, Sandeep Subramanian, Kazuya Kawakami, and Chris Dyer, “Neural architectures for named entity recognition,” in Proceedings of NAACL-HLT, 2016, pp. 260–270 … The intent schema specifies the intents supported by a skill …

Key-Value Retrieval Networks for Task-Oriented Dialogue
M Eric, CD Manning – arXiv preprint arXiv:1705.05414, 2017 – arxiv.org
… Task-oriented agents for spoken dialogue systems have been the subject of extensive research … These models learn to explicitly represent user intent through interme- diate supervision, which … surface expression of entities to a canonical form using named entity recognition and …

RubyStar: A Non-Task-Oriented Mixture Model Dialog System
H Liu, T Lin, H Sun, W Lin, CW Chang, T Zhong… – arXiv preprint arXiv …, 2017 – arxiv.org
… Examples for each intent were based on our corpus labeling results. Finally, we select different conversation strategies depending on the intent: for some intents, we select … This module consists of an Named Entity Disambiguation (NED) model and a template selection model …

Two-stage multi-intent detection for spoken language understanding
B Kim, S Ryu, GG Lee – Multimedia Tools and Applications, 2017 – Springer
… Most studies design meaning representation as a combination of an intent and named entities in a given domain [2, 7, 8, 19, 24] … We categorize those sentences as single intent (SI)-type. However, in the real world, users often express multiple intents (MIs) within one dialog turn …

Cluster-Based Graphs for Conceiving Dialog Systems
JL Bouraoui, V Lemaire – … DMNLP at European Conference on Machine …, 2017 – ceur-ws.org
… Some of the clusters were also used to represent the intents of the users … allows to consider the speech turns of this cluster as some different formulations of the intent … optimizations of the corpus: for example, the lemmatization of words or the neutralization of Named Entities …

Evaluating natural language understanding services for conversational question answering systems
D Braun, A Hernandez-Mendez, F Matthes… – Proceedings of the 18th …, 2017 – aclweb.org
… for differ- ent purposes, eg question answering for localized search (McTear et al., 2016), form-driven dialogue systems (Stoyanchev et al … basic concept: Based on example data, the user can train a classifier to classify so-called intents (which represent the intent of the …

A knowledge graph based speech interface for question answering systems
AJ Kumar, C Schmidt, J Köhler – Speech Communication, 2017 – Elsevier
… speech recognition, while SLU specific problems include slot filling and intent detection, entity … ABIONET NE Recogniser and Classifiers are used to tag named entities with basic … environment and elaborates how SALT can be used to implement multimodal dialogue systems …

Combining Search with Structured Data to Create a More Engaging User Experience in Open Domain Dialogue
KK Bowden, S Oraby, J Wu, A Misra… – arXiv preprint arXiv …, 2017 – arxiv.org
… foregrounds many longstanding challenges that have not been solved even for task-oriented dialogue systems … Names a particular film, named entity recognition must map “Jason Bourne” to a movie entity … dialogue acts are extremely varied at each turn, eg user intents can be …

A cognitive system for business and technical support: A case study
P Dhoolia, P Chugh, P Costa… – IBM Journal of …, 2017 – ieeexplore.ieee.org
… knowledge graph notion [40–42] focuses on entity resolution, where a named entity, eg, “Taj … based on the action being performed, the possibilities regarding support intent and errors … focus on a corpus comprising error-messages and questions mapped to the support intents …

Towards improving the performance of chat oriented dialogue system
R Jiang, RE Banchs – Asian Language Processing (IALP), 2017 …, 2017 – ieeexplore.ieee.org
… This paper is concerned with how to improve the overall performance of chat-oriented dialogue system … toolNit such as the POS tags, the coreference resolution, and named entity recognition, they … subsections are helpful for the chatbot to discover user’s overall intent as well as …

Flexible End-to-End Dialogue System for Knowledge Grounded Conversation
W Zhu, K Mo, Y Zhang, Z Zhu, X Peng… – arXiv preprint arXiv …, 2017 – arxiv.org
… 2015) proposed a rule-based dialogue system by filling the response tem- plates with retrieved KB … 2. A message encoder encodes the input message X into a set of intent vectors at … song), or detected by more advanced methods such as entity linking or named entity recognition …

Alquist: An Open-Domain Dialogue System
J Pichl – radio.feld.cvut.cz
… Page 2. 2 J. Pichl, Alquist Dialogue System … The easiest way is when the sequence of words from the input sentence is marked as a named entity (NE) … This decision is based on the user’s intent. The intent is estimated as follows …

LD-SDS: Towards an Expressive Spoken Dialogue System based on Linked-Data
A Papangelis, P Papadakos, M Kotti… – arXiv preprint arXiv …, 2017 – arxiv.org
… To process the complex intent of the user, we connect our SDS with Hippalus, an exploratory search … In order to process input that reflects complex user intents (and may have different meanings for different … Exploiting linked data for open and configurable named entity extraction …

Underspecification in Natural Language Understanding for Dialog Automation
J Chen, S Bangalore – … of the International Conference Recent Advances …, 2017 – acl-bg.org
… Its dif- ficulty is similar to that of named entity recogni- tion or entity linking … Classification Task Baseline Accuracy Intents 41.85 90.65 Entities 35.59 93.92 Conversational 90.81 99.01 Joint 7.41 … In contrast, accuracies of intent and entity classifiers increase more quickly as more …

Roving Mind: a balancing act between open–domain and engaging dialogue systems
A Cervone, G Tortoreto, S Mezza, E Gambi, G Riccardi – researchgate.net
… Hence, in RM each FU is represented by an intent, that is a DA structure composed by a DA … the system pipeline for the segmentation into functional units and identification of user intents, and entity … First, the ASR output is case-restored to improve the detection of Named Entities …

Using Knowledge Graph And Search Query Click Logs in Statistical Language Model For Speech Recognition
W Zhu – Proc. Interspeech 2017, 2017 – isca-speech.org
… Utiliz- ing relationships between named entities to improve speech recog- nition in dialog systems,” in Spoken … [18] J. Horlock and S. King, “Named entity extraction from … and L. Heck, “Extending domain coverage of language understand- ing systems via intent transfer between …

Leveraging Conversational Systems to Assists New Hires During Onboarding
P Chandar, Y Khazaeni, M Davis, M Muller… – IFIP Conference on …, 2017 – Springer
… chit chat and knowledge base question category into more granular intents was more … Entity Extraction: Additionally, each user request was also annotated with named entities and keywords … with this average accuracy, subjective evaluation indicated a users’ intent for continued …

A Chatbot by Combining Finite State Machine, Information Retrieval, and Bot-Initiative Strategy
S Yi, K Jung – sanghyunyi.ml
… Finally, we made an intent which makes use of Evi to handle greetings from users … First, it detects keywords or named-entities(NE) from the input sentence … to the conversation which is obtained from a keyword dictionary or a SVM classifier(See descriptions about intents in Section …

Tracking of enriched dialog states for flexible conversational information access
Y Dai, Z Ou, D Ren, P Yu – arXiv preprint arXiv:1711.03381, 2017 – arxiv.org
… slots, #values is the number of all the values in ontoloty, #named entity is the … and Steve Young, “A network-based end-to-end trainable task- oriented dialogue system,” in EACL … and Ruhi Sarikaya, “Convolutional neural network based triangular crf for joint intent detection and …

Collaboration-based User Simulation for Goal-oriented Dialog Systems
D Didericksen, ORKSL Zhou, J Kramer – alborz-geramifard.com
… data using standard methods – tokenization, lemmatization, removing stop words, and substituting named entities with placeholders … explicitly predict the next user action, we are using the intent of the … Therefore, if we had the user intents explicitly annotated, we could operate on …

“nee intention enti?” towards dialog act recognition in code-mixed conversations
DS Jitta, KR Chandu, H Pamidipalli… – Asian Language …, 2017 – ieeexplore.ieee.org
… the sentence is embedded plays an important role in understanding the intent of the … be used for the purpose of intention recognition in a task oriented dialog system … categories, namely En- glish, Telugu, Mixed (morpheme level mixing), acronyms, named-entities and unknown …

Joint Learning of Dialog Act Segmentation and Recognition in Spoken Dialog Using Neural Networks
T Zhao, T Kawahara – Proceedings of the Eighth International Joint …, 2017 – aclweb.org
… of dialog system, is usually responsible for dialog act (DA) or dialog intent tagging, where … Therefore DA segmentation becomes essential for spoken dialog systems … higher-level tasks usually depend on outputs from lower-level tasks, for example named entity recognition (NER …

A Survey on Dialogue Systems: Recent Advances and New Frontiers
H Chen, X Liu, D Yin, J Tang – arXiv preprint arXiv:1711.01731, 2017 – arxiv.org
… The other is the word-level information extraction such as named entity recognition and slot filling. An intent detection is performed to detect the intent of a user … intents. Deep learning techniques have been successively applied in intent detection [10; 73; 99] …

Negotiation of Antibiotic Treatment in Medical Consultations: A Corpus based Study
N Wang – Proceedings of ACL 2017, Student Research …, 2017 – aclweb.org
… Current research for dialogue systems offer an alternative ap- proach … 5.1.1 Named Entity Recognition Entities are very important in spoken language un- derstanding, as it conveys key information in de- termining task objectives, intents, etc …

Remembering what you said: Semantic personalized memory for personal digital assistants
V Agarwal, OZ Khan, R Sarikaya – Acoustics, Speech and …, 2017 – ieeexplore.ieee.org
… The queries also had various intents (asking for directions, phone number, address, open … Sarikaya, and Eric Fosler- Lussier, “Knowledge graph inference for spoken dialog systems,” in ICASSP … learning of the embedding of words and entities for named entity disambiguation,” in …

Learning Generative End-to-end Dialog Systems with Knowledge
T Zhao – 2017 – cs.cmu.edu
… Page 2. November 21, 2017 DRAFT Keywords: dialog systems, end-to-end models, deep learning, reinforcement learn- ing, generative models, transfer learning, zero-shot learning Page 3 … Page 17. November 21, 2017 DRAFT Chapter 2 Related Work 2.1 Dialog Systems …

Anjishnu Kumar Amazon. com anjikum@ amazon. com
S Tucker, B Hoffmeister, M Dreyer, S Peshterliev… – alborz-geramifard.com
… [31] Guillaume Lample, Miguel Ballesteros, Sandeep Subramanian, Kazuya Kawakami, and Chris Dyer, “Neural architectures for named entity recognition,” in Proceedings of NAACL-HLT, 2016, pp. 260–270 … The intent schema specifies the intents supported by a skill …

Improving the Memory of Intelligent Personal Assistants
LJ Peter – 2017 – researchgate.net
… Related pieces of information could clue in on user intent when terms are ambiguous.4 … people that share certain first names, last names, or other properties. An utterance passes to dialogue system, through the NLU, and Chelsie is recognized as a named entity …

Production Ready Chatbots: Generate if not Retrieve
A Tammewar, M Pamecha, C Jain, A Nagvenkar… – arXiv preprint arXiv …, 2017 – arxiv.org
… The queries/intents and responses on a particular state are finite in number … define the intent of the state and predefined set of slot filling table which map to responses to gather the … Entities: Using an in-house built NER, we re- place the original text of the named entities such as …

Building CMU Magnus from User Feedback
S Prabhumoye, F Botros, K Chandu… – Alexa Prize …, 2017 – nzini.com
… Store the person and location named-entities so that we can retrieve the … At times, the user conveys intents that are not captured by our FST model … Do you not like such genres?’. Hence, the intent conveyed by the user is lost and the FST responds inappropriately. 4 Stage 3 …

Bringing Semantic Structures to User Intent Detection in Online Medical Queries
C Zhang, N Du, W Fan, Y Li, CT Lu, PS Yu – arXiv preprint arXiv …, 2017 – arxiv.org
Page 1. Bringing Semantic Structures to User Intent Detection in Online Medical Queries Chenwei Zhang?¶, Nan … text queries. Index Terms—Information Search; Intent Detection; Concept Transition; Neural Network 1. Introduction The …

Learning discourse-level diversity for neural dialog models using conditional variational autoencoders
T Zhao, R Zhao, M Eskenazi – arXiv preprint arXiv:1703.10960, 2017 – arxiv.org
… Our model uses latent vari- ables to learn a distribution over potential conversational intents and generates diverse responses using only greedy … 1 Introduction The dialog manager is one of the key components of dialog systems, which is responsible for mod- eling the decision …

The commercial NLP landscape in 2017
R Dale – Natural Language Engineering, 2017 – cambridge.org
… similar to the much older category of telephony-based spoken language dialogue systems that let … provide learned classification of user utterances into a smaller set of intents that will … all of these are provided by every vendor in the space, are named entity recognition, concept …

A Continuous Relaxation of Beam Search for End-to-end Training of Neural Sequence Models
K Goyal, G Neubig, C Dyer… – arXiv preprint arXiv …, 2017 – arxiv.org
… Macro F1 over the prediction of different named entities is reported that is a standard … search during training actually may achieve the opposite of our original intent: the objective can … Y. Bengio, A. Courville, and J. Pineau, “Building end-to-end dialogue systems using generative …

Syntax and Semantics Question Analysis Using User Modelling and Relevance Feedback
A Saany, I Syarilla, A Mamat, A Mustapha… – … Journal on Advanced …, 2017 – media.neliti.com
… By using named entity parameter, the pseudo relevance feedback can help the users to target the relevant documents at the top rank and eliminate the non … Here, a better performance QA means the system is able to return a correct answer based on user’s intent question …

Mixed-initiative intent recognition using cloud-based cognitive services
M Kraus – 2017 – oparu.uni-ulm.de
… All of the components of the dialogue system are embedded in the Microsoft Bot Framework … of a model starts with creating a LUIS application, which is based on the concepts of intents and entities: Intent describes the intention of a user in an utterance (Williams et al., 2015) …

Knowledge Guided Short-Text Classification for Healthcare Applications
S Cao, B Qian, C Yin, X Li, J Wei… – Data Mining (ICDM) …, 2017 – ieeexplore.ieee.org
… It is not easy for a chatbot to identify the user’s intents, since the unknown medical entities … 1 shows, the chatbot faces a big challenge to determine the user’s intent in a typical dialog … It aims to locate and classify named entities in text into pre-defined categories such as the …

Encoder-decoder with focus-mechanism for sequence labelling based spoken language understanding
S Zhu, K Yu – … , Speech and Signal Processing (ICASSP), 2017 …, 2017 – ieeexplore.ieee.org
… In a spoken dialogue system, the Spoken Language Under- standing (SLU) is a key … in sequence labelling typically consists of three tasks: domain detection, intent determination and slot … to other sequence labelling tasks (eg part-of-speech tagging, named entity recognition) …

Ask Me Anything: A Conversational Interface to Augment Information Security Workers
B Filar, RJ Seymour, M Park – … on Usable Privacy and Security (SOUPS), 2017 – usenix.org
… Conversational interfaces or dialog systems have been suc- cessfully employed in a variety of domains … In NLU this tagging process is known as Named Entity Recog- nition (NER) … This allows the next step of intent classification to model a reduced vocab- ulary …

Evaluation of Modern Tools for an OMSCS Advisor Chatbot
E Gregori – 2017 – smartech.gatech.edu
… Named entity recognition means finding spans of text that constitute proper names and then classifying the type of … The IA algorithm must be trained to categorize sentences into intents. A list of sentences with similar intent (but worded differently) is passed to the algorithm and …

Utilizing bots in delivering content from Kentico Cloud and Kentico EMS
A Eikonsalo – 2017 – tampub.uta.fi
… like POS tagging in a sense since it identifies and labels the words or sentences that refer to named entities such as people, brands, or company names … For the intent to be triggered, all the contexts defined for the intent must be active. It is possible to prioritize the intents in …

A Survey of Design Techniques for Conversational Agents
K Ramesh, S Ravishankaran, A Joshi… – International Conference …, 2017 – Springer
… Actions correspond to the steps the chatbot will take when specific intents are triggered by user … when a user says “Switch it off” as the succeeding input, the intent “switch off … chat query is processed by performing stemming, part-of-speech tagging and named entity recognition …

A Survey of Design Techniques for Conversational Agents
K Chandrasekaran – … Conference, ICICCT 2017, New Delhi, India …, 2017 – books.google.com
… Actions correspond to the steps the chatbot will take when specific intents are triggered by user … when a user says “Switch it off” as the succeeding input, the intent “switch off … chat query is processed by performing stemming, part-of-speech tagging and named entity recognition …

Using Context Information for Dialog Act Classification in DNN Framework
Y Liu, K Han, Z Tan, Y Lei – Proceedings of the 2017 Conference on …, 2017 – aclweb.org
… as well as for developing intel- ligent human-to-computer dialog systems (either written or … for various sequence labeling problems (such as part-of-speech tagging, named entity recognition) and … we plan to apply these approaches to other tasks, such as intent recognition and …

Dialogue Act Segmentation for Vietnamese Human-Human Conversational Texts
TL Ngo, KL Pham, MS Cao, SB Pham… – arXiv preprint arXiv …, 2017 – arxiv.org
… It is important for many applications: dialogue systems, automatic translation machine [2], automatic speech … standard form, in this case, the intent conveyed by the utterance would be … Subramanian, S., Kawakami, K., Dyer, C. “Neural architectures for named entity recognition.” …

I Probe, Therefore I Am: Designing a Virtual Journalist with Human Emotions
KK Bowden, T Nilsson, CP Spencer, K Cengiz… – arXiv preprint arXiv …, 2017 – arxiv.org
… were continuously carried out in parallel to the development of the dialogue system in order to … knowledge base for important nodes within the sentence such as the named entities, proper nouns … behavior defined in Flipper’s templates, the agent would formulate its intent, ie how …

A study on integrating distinct classifiers with bidirectional LSTM for Slot Filling task
KP Do – 2017 – dspace.jaist.ac.jp
… there are three vital tasks in SLU with respect to semantic extraction of input utterances namely domain detection, intent determination, and slot … An example sentence is illustrated in Table 2.1, along with domain, slot annotations, and special domain-independent named entity …

Sabbiu Shah (070/BCT/531) Sagar Adhikari (070/BCT/533) Samip Subedi (070/BCT/536)
U Chalise – 2017 – researchgate.net
… Chatterbots are typically used in dialog systems for various practical purposes including customer service or … etc.) in order to solve properly. • Named Entity Recognition(NER) … the intent of user message.It is selection of one out of a number of predefined intents.Intent …

Semantic specialisation of distributional word vector spaces using monolingual and cross-lingual constraints
N Mrkši?, I Vuli?, DÓ Séaghdha, I Leviant… – arXiv preprint arXiv …, 2017 – arxiv.org
… To the best of our knowledge, this is the first work on multilingual training of any compo- nent of a statistical dialogue system … We made use of all BabelNet word senses tagged as conceptual but ignored the ones tagged as Named Entities …

Automatic sarcasm detection: A survey
A Joshi, P Bhattacharyya, MJ Carman – ACM Computing Surveys (CSUR …, 2017 – dl.acm.org
Page 1. 73 Automatic Sarcasm Detection: A Survey ADITYA JOSHI, IITB-Monash Research Academy PUSHPAK BHATTACHARYYA, Indian Institute of Technology Bombay MARK J. CARMAN, Monash University Automatic sarcasm …

Neural Models for Sequence Chunking.
F Zhai, S Potdar, B Xiang, B Zhou – AAAI, 2017 – aaai.org
… (Huang, Xu, and Yu 2015) presented a BiLSTM-CRF model, and achieved state-of-the-art performance on several tasks, like named entity recognition and text chunking with the help of handcrafted features … Chiu, JP, and Nichols, E. 2015. Named entity recognition with bidirecti

Towards a top-down policy engineering framework for attribute-based access control
M Narouei, H Khanpour, H Takabi, N Parde… – Proceedings of the …, 2017 – dl.acm.org
… frequency in a variety of text processing applications, from sentiment analysis [41] to conversational text processing for dialogue systems [22, 48] … neural networks (CNNs) to develop an e cient application for part-of-speech tagging, chunk- ing, named entity recognition, semantic …

Science Driven Innovations Powering Mobile Product: Cloud AI vs. Device AI Solutions on Smart Device
D Kong – arXiv preprint arXiv:1711.07580, 2017 – arxiv.org
… Personal Assistant Engine on Mobile Device ? Dialog System ? Speech recognition ? Speech synthesis ? NLP understanding ? Chatbot … Fig. shows the different stages in marketing funnel, ie, Awareness ? interest ? consideration ? intent ? evaluation ? purchase …

SHERLOCK: Experimental evaluation of a conversational agent for mobile information tasks
A Preece, W Webberley, D Braines… – … on Human-Machine …, 2017 – ieeexplore.ieee.org
… IV. USER EVALUATION The primary intent of the user evaluation was to gather ev- idence for whether the CNL-based approach to HCC on in- formation tasks described in the previous section can be used effectively by users, with low training overheads …

Learning Semantic Patterns for Question Generation and Question Answering
HP Rodrigues – 2017 – pdfs.semanticscholar.org
… domains, such as in creation of dialog systems [Nio et al., 2014] or translation of unknown words [Langlais and Patry, 2007]. Despite recent progresses, the used pattern methods usually only go to the lexical and syntactic level, sometimes adding Named Entities and Semantic …

Automatic question generation for virtual humans
EL Fasya – 2017 – essay.utwente.nl
… manager in a spoken dialogue system [2]. 2.3.2 Form-based … intent. For example, when the intent is asking an information about the white rabbit, the … names of miscellaneous entities – which is assigned on each recognizable named entity. The …

Neural Logic Framework for Digital Assistants
N Cingillioglu, A Russo, K Broda – 2017 – imperial.ac.uk
… extraction and named entity recognition have been addressed by academics as well as by … storing facts, intent parsing and deduction (chapter 4) … to checkout procedures triggered by intents or key phrases in the case of Converse AI [26] …

Painting Pictures with Words-From Theory to System
R Coyne – 2017 – search.proquest.com
… example of a system that generates visualizations that are automatically composed to convey intent … Ulysse [Godreaux et al., 1999] is an interactive spoken dialog system used to navigate … It also performs domain-specic named entity recognition to handle the locations (eg cities …

D1. 4-Final Project Management Report
DB WIT, MT WIT, O Uryupina – cognet.5g-ppp.eu
Page 1. D1.4- Final Project Management Report Document Number D1.4 Status Final Work Package WP 1 Deliverable Type Report Date of Delivery 31/12/2017 Period Covered 1st July 2015 – 31st December 2017 Responsible Unit WIT …

Linguistic Knowledge Transfer for Enriching Vector Representations
JK Kim – 2017 – rave.ohiolink.edu
… ii Page 4. Long Short-Term Memory (BLSTM) model for intent detection, which is a sentence-level downstream task especially when only small numbers of training examples are available … 4 Page 23. 1.1.3 Enriching word embeddings for intent detection (Chapter 5) …

Design and development of a cognitive assistant for the architecting of earth observing satellites
A Virós Martin – 2017 – upcommons.upc.edu
… ing a pilot’s situational awareness during a flight [57]. The CA is capable of understanding the flight situation and combine that with the intent of the pilot to keep a human-like communication with him/her to ensure their situ- ational awareness …

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