Challenge: ISO 24617-2 is the ISO standard for dialog act annotation.
Approach: They map the original dialog act labels of the LEGO corpus into the communicative functions of ISO 24617-2 . they propose to use this data to develop approaches for dialog act recognition .
Outcome: The mapped dialogs improve performance while recognizing communicative functions . the standard is based on 17 English dialogs, which are used in the study .

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The ADELE Corpus of Dyadic Social Text Conversations:Dialog Act Annotation with ISO 24617-2 (L18-1)

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Challenge: Recent studies have focused on task-based or instrumental dialogs, but there is increasing interest in social or interactional dialogs.
Approach: They describe a corpus of 193 dyadic text dialogs based on a novel 'getting to know you' social dialog elicitation paradigm and propose additional acts to better cover greeting and leavetaking.
Outcome: The proposed actions cover greeting and leavetaking, and the proposed acts improve the interaction between the dialogs and spoken language.
The ISO Standard for Dialogue Act Annotation, Second Edition (2020.lrec-1)

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Challenge: ISO standard 24617-2 for dialogue act annotation has been used in corpus annotation and in the design of components for spoken and multimodal interactive systems.
Approach: ISO standard 24617-2 for dialogue act annotation is proposed for a second edition . this second edition allows a more accurate annotation of dependence relations and rhetorical relations in dialogue.
Outcome: The proposed second edition of ISO 24617-2 for dialogue act annotation addresses some inaccuracies and undesirable limitations.
A Vietnamese Dialog Act Corpus Based on ISO 24617-2 standard (L18-1)

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Challenge: standardized dialog act corpora are used for conversation mining research . different corporations often use different methods to understand interaction structure .
Approach: They propose to annotate dialog acts using ISO 24617-2 standard (2012) . they also annotated emotions using Ekman's six primitives and sentiment using tags "positive", "negative" and "neutral"
Outcome: The proposed corpus is constructed using the ISO 24617-2 standard (2012) . it is used for emotions, sentiment and positive, negative and neutral tags .
ISO-Standard Domain-Independent Dialogue Act Tagging for Conversational Agents (C18-1)

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Challenge: Existing methods for DA annotation are incompatible with each other and do not cover all aspects necessary for open-domain human-machine interaction.
Approach: They propose to map publicly available corpora to a subset of the ISO standard and create a task-independent training corpus for DA classification.
Outcome: The proposed method can train a domain-independent DA tagger on out-of-domain conversational data and achieve robustness across different DA categories.
An Evaluation Dataset for Identifying Communicative Functions of Sentences in English Scholarly Papers (2020.lrec-1)

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Challenge: Formulaic expressions are used by authors of scientific papers because they convey specific communicative functions in the rhetorical structure of papers.
Approach: They created a manually annotated dataset to detect formulaic expressions in sentences using a seed list of labelled formulaic words.
Outcome: The proposed dataset can detect communicative functions in sentences using a seed list of labelled expressions from scholarly papers in the ACL Anthology.
A Multi-Dimensional, Cross-Domain and Hierarchy-Aware Neural Architecture for ISO-Standard Dialogue Act Tagging (2022.coling-1)

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Challenge: Dialogue Act tagging with ISO 24617-2 standard is a difficult task that requires multiple labels covering semantic, syntactic and pragmatic aspects of dialogue.
Approach: They propose a neural architecture to increase Dialogue Act tagging accuracy by using low-frequency fine-grained tags.
Outcome: The proposed model achieves state-of-the-art tagging results on DialogBank data set . it uses syntactic information in the form of Part-Of-Speech and dependency tags .
MIDAS: A Dialog Act Annotation Scheme for Open Domain HumanMachine Spoken Conversations (2021.eacl-main)

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Challenge: Existing dialog act schemes are designed for human-human conversations, but are not suitable for automatic speech recognition.
Approach: They propose a dialog act annotation scheme for open-domain human-machine conversations . they collected 24K utterances from a large open- domain spoken conversation dataset .
Outcome: The proposed scheme achieves an F1 score of 0.79 on a 24K spoken conversation dataset.
What Helps Transformers Recognize Conversational Structure? Importance of Context, Punctuation, and Labels in Dialog Act Recognition (2021.tacl-1)

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Challenge: Existing punctuation in the transcripts has a massive effect on the models’ performance, and specific label set specificity does not affect dialog act segmentation performance.
Approach: They apply two pre-trained transformer models to a conversation transcript as a sequence of dialog acts and achieve strong results on Switchboard Dialog Act and Meeting Recorder Dialog Act corpora.
Outcome: The proposed models achieve 8.4% and 14.2% error rates on the Switchboard Dialog Act and Meeting Recorder Dialog Act corpora.
ISO 24617-12: A New Standard for Semantic Annotation (2024.lrec-main)

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Challenge: ISO 24617-12 is a proposed new standard 1 for the annotation of quantification phenomena in natural language.
Approach: This paper proposes an annotation scheme for quantification phenomena in natural language as part of the ISO Semantic Annotation Framework (ISO 24617) it combines ideas from the theory of generalised quantifiers, from neo-Davidsonian event semantics, and from Discourse Representation Theory.
Outcome: The proposed standard 1 is an annotation scheme for quantification phenomena in natural language.
Annotation Process for the Dialog Act Classification of a Taglish E-commerce Q&A Corpus (D19-51)

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Challenge: Existing studies on DA classification in general contexts have not addressed this problem.
Approach: They constructed a text-based corpus of 7,265 posts from the question and answer section of products on Lazada Philippines.
Outcome: The text-based corpus of 7,265 posts from the question and answer section of products on Lazada Philippines was constructed using a tagset for DA classification . the corpus was composed dominantly of single-label posts, with 34% of the corpuse having multiple intent tags.

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