Automatic minuting: A pipeline method for generating minutes from multi-party meeting proceedings

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3A10457090" target="_blank" >RIV/00216208:11320/22:10457090 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.paclic2022.net/papers.html" target="_blank" >https://www.paclic2022.net/papers.html</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Automatic minuting: A pipeline method for generating minutes from multi-party meeting proceedings

Popis výsledku v původním jazyce

Automatically generating meeting minutes is a challenging yet time-relevant problem in speech and natural language processing. Nowadays, meeting minutes seem more cru- cial than ever due to the manifold rise of on- line meetings. However, automatic minut- ing is not straightforward for various reasons: obtaining transcriptions of sufficient quality, summarizing long dialogue discourse, retain- ing topical relevance and coverage, handling redundancies and small talk, etc. This pa- per presents our investigations on a pipelined approach to automatically generate meeting minutes using a BART model (Bidirectional and Auto-Regressive Transformers) trained on multi-party dialogue summarization datasets. We achieve comparable results with our sim- ple yet intuitive method with respect to pre- vious large and computationally heavy state- of-the-art models. We make our code avail- able at https://github.com/ELITR/ minuting-pipeline.

Název v anglickém jazyce

Automatic minuting: A pipeline method for generating minutes from multi-party meeting proceedings

Popis výsledku anglicky

Automatically generating meeting minutes is a challenging yet time-relevant problem in speech and natural language processing. Nowadays, meeting minutes seem more cru- cial than ever due to the manifold rise of on- line meetings. However, automatic minut- ing is not straightforward for various reasons: obtaining transcriptions of sufficient quality, summarizing long dialogue discourse, retain- ing topical relevance and coverage, handling redundancies and small talk, etc. This pa- per presents our investigations on a pipelined approach to automatically generate meeting minutes using a BART model (Bidirectional and Auto-Regressive Transformers) trained on multi-party dialogue summarization datasets. We achieve comparable results with our sim- ple yet intuitive method with respect to pre- vious large and computationally heavy state- of-the-art models. We make our code avail- able at https://github.com/ELITR/ minuting-pipeline.

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

2022

Kód důvěrnosti údajů

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