An Empirical Performance Analysis of State-of-the-Art Summarization Models for Automatic Minuting

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10456914" target="_blank" >RIV/00216208:11320/21:10456914 - isvavai.cz</a>

Výsledek na webu

<a href="https://aclanthology.org/2021.paclic-1.6/" target="_blank" >https://aclanthology.org/2021.paclic-1.6/</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

An Empirical Performance Analysis of State-of-the-Art Summarization Models for Automatic Minuting

Popis výsledku v původním jazyce

A significant portion of the working population has their mainstream interaction virtually these days. Meetings are being organized and recorded daily in volumes likely exceeding what can be ever comprehended. With the deluge of meetings, it is important to identify and jot down the essential items discussed in the meeting, usually referred to as the minutes. The task of minuting is diverse and depends on the goals, style, procedure, and category of the meeting. Automatic Minuting is close to summarization; however, not exactly the same. In this work, we evaluate the current state-of-the-art summarization models for automatically generating meeting minutes. We provide empirical baselines to motivate the community to work on this very timely, relevant yet challenging problem. We conclude that off-the-shelf text summarization models are not the best candidates for generating minutes which calls for further research on meeting-specific summarization or minuting models. We found that Transformerbased mode

Název v anglickém jazyce

An Empirical Performance Analysis of State-of-the-Art Summarization Models for Automatic Minuting

Popis výsledku anglicky

A significant portion of the working population has their mainstream interaction virtually these days. Meetings are being organized and recorded daily in volumes likely exceeding what can be ever comprehended. With the deluge of meetings, it is important to identify and jot down the essential items discussed in the meeting, usually referred to as the minutes. The task of minuting is diverse and depends on the goals, style, procedure, and category of the meeting. Automatic Minuting is close to summarization; however, not exactly the same. In this work, we evaluate the current state-of-the-art summarization models for automatically generating meeting minutes. We provide empirical baselines to motivate the community to work on this very timely, relevant yet challenging problem. We conclude that off-the-shelf text summarization models are not the best candidates for generating minutes which calls for further research on meeting-specific summarization or minuting models. We found that Transformerbased mode

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GX19-26934X" target="_blank" >GX19-26934X: Neuronové reprezentace v multimodálním a mnohojazyčném modelování</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů