Challenge: Existing methods for training doctors to break bad news are expensive and time consuming.
Approach: They propose a method to collect a corpus of human-machine interactions and then construct a semi-autonomous system based on the collected corpus.
Outcome: The proposed system is based on a corpus-based method to analyze human-machine interactions and then develop fully autonomous prototype.

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A French Medical Conversations Corpus Annotated for a Virtual Patient Dialogue System (2020.lrec-1)

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Challenge: Existing methods for creating virtual patient dialogue systems require large data specific to the language, domain and clinical cases studied.
Approach: They propose to build an annotated corpus of medical dialogues in french using medical interviews and a data annotation scheme.
Outcome: The proposed corpus is made publicly available under a Free/Libre Open Source licence.
Towards Continuous Dialogue Corpus Creation: writing to corpus and generating from it (L18-1)

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Challenge: Existing methods to create dialogue corpora annotated with interoperable semantic information are based on ISO standard data models and tools.
Approach: They propose to use a corpus as a shared repository for analysis and modelling of interactive dialogue behaviour and for implementation, integration and evaluation of dialogue system components.
Outcome: The proposed method is applied to the design of two multimodal interactive applications - the Virtual Negotiation Coach and the Virtual Debate Coach.
An Information-Providing Closed-Domain Human-Agent Interaction Corpus (L18-1)

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Challenge: a human-agent interaction corpus is a corpus of conversations between a user and an embodied conversational agent operated by a wizard of oz . data collected to create a 'corpus' with unexpected situations, such as misunderstandings, false information, and interruptions.
Approach: They propose a public corpus for Human-Agent Interaction where the agent is controlled by a Wizard of Oz.
Outcome: The proposed corpus is based on 15 conversations between users and a wizard of Oz agent . the data are used to create a corpus with unexpected situations, such as misunderstandings, false information, and interruptions.
A Brief Survey of Textual Dialogue Corpora (2022.lrec-1)

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Challenge: Several dialogue corpora are available for research purposes, but they do not cover all the necessities of real-world applications.
Approach: They analyze available dialogue corpora and propose possible approaches to create new ones.
Outcome: The proposed corpus of human-human dialogues is based on a list of available dialogue corpora . it covers speakers, size, languages, collection, annotations, and domains . some trends are identified and possible approaches are also discussed .
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 3: System Demonstrations) (2024.naacl-demo)

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Challenge: The System Demonstration Track at NAACL 2024 is a platform for presenting papers that describe system demonstrations.
Approach: the system demonstration track at NAACL 2024 is taking place from June 16 to June 21.
Outcome: the system demonstration track at NAACL 2024 received 48 submissions this year . the acceptance rate was 43 .
A Persona-Based Corpus in the Diabetes Self-Care Domain - Applying a Human-Centered Approach to a Low-Resource Context (2024.lrec-main)

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Challenge: Human-centered design (HCD) is a new approach to natural language processing that uses personas, user profiles and other tools to build corpus.
Approach: They propose to use personas to model interpersonal interaction in a healthcare domain to follow an HCD approach.
Outcome: The proposed model improves the quality of human-centered design in a healthcare domain and overcomes the lack of in-depth human-centricity in the field.
The AI Doctor Is In: A Survey of Task-Oriented Dialogue Systems for Healthcare Applications (2022.acl-long)

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Challenge: Task-oriented dialogue systems have been surveyed in the medical community from a non-technical perspective, but a systematic review from . a rigorous computational perspective has to date remained noticeably absent.
Approach: They analyze 4070 papers on task-oriented dialogue systems for healthcare applications and identify gaps in their analysis.
Outcome: The proposed system-level implementation details remain limited or underspecified, slowing the pace of innovation in this area.
The Brain-IHM Dataset: a New Resource for Studying the Brain Basis of Human-Human and Human-Machine Conversations (2020.lrec-1)

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Challenge: Using a dataset of controlled interactions, we have studied the feedback items produced by the interlocutors during a conversation.
Approach: They propose to use a dataset of controlled interactions to study feedback items and a virtual reality context to re-synthesize the conversations.
Outcome: The proposed dataset compares human-human and human-machine production of feedbacks and is the first of its kind.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations) (2023.acl-demo)

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Challenge: 58 papers were selected for inclusion in the program, while a small number received only two reviews.
Approach: the 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023) will be held in london from July 9-14, 2023 . 58 submissions were selected for inclusion in the program, with an acceptance rate of 37%)
Outcome: the system demonstration track received a record number of submissions . 58 papers were selected for inclusion in the program .
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations) (2025.acl-demo)

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Challenge: ACL 2025 System Demonstration Track accepted 64 papers based on reviews . short-listed 7 papers for Best System Demo award .
Approach: the ACL 2025 System Demonstration Track is a conference for papers describing system demonstrations . the track received a record 187 submissions, of which 178 papers were valid with required materials .
Outcome: the ACL 2025 System Demonstration Track received 187 submissions . 178 papers were valid with required materials .

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