TY - GEN
T1 - ELITR Minuting Corpus
T2 - 13th International Conference on Language Resources and Evaluation Conference, LREC 2022
AU - Nedoluzhko, Anna
AU - Singh, Muskaan
AU - Hledíková, Marie
AU - Ghosal, Tirthankar
AU - Bojar, Ondřej
N1 - Publisher Copyright:
© European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0.
PY - 2022
Y1 - 2022
N2 - Taking minutes is an essential component of every meeting, although the goals, style, and procedure of this activity (“minuting” for short) can vary. Minuting is a relatively unstructured writing act and is affected by who takes the minutes and for whom the minutes are intended. With the rise of online meetings, automatic minuting would be an important use-case for the meeting participants and those who might have missed the meeting. However, automatically generating meeting minutes is a challenging problem due to various factors, including the quality of automatic speech recognition (ASR), public availability of meeting data, subjective knowledge of the minuter, etc. In this work, we present the first of its kind dataset on Automatic Minuting. We develop a dataset of English and Czech technical project meetings, consisting of transcripts generated from ASRs, manually corrected, and minuted by several annotators. Our dataset, ELITR Minuting Corpus, consists of 120 English and 59 Czech meetings, covering about 180 hours of meeting content. The corpus is publicly available at http://hdl.handle.net/11234/1-4692 as a set of meeting transcripts and minutes, excluding the recordings for privacy reasons. A unique feature of our dataset is that most meetings are equipped with more than one minute, each created independently. Our corpus thus allows studying differences in what people find important while taking the minutes. We also provide baseline experiments for the community to explore this novel problem further. To the best of our knowledge, ELITR Minuting Corpus is probably the first resource on minuting in English and also in a language other than English (Czech).
AB - Taking minutes is an essential component of every meeting, although the goals, style, and procedure of this activity (“minuting” for short) can vary. Minuting is a relatively unstructured writing act and is affected by who takes the minutes and for whom the minutes are intended. With the rise of online meetings, automatic minuting would be an important use-case for the meeting participants and those who might have missed the meeting. However, automatically generating meeting minutes is a challenging problem due to various factors, including the quality of automatic speech recognition (ASR), public availability of meeting data, subjective knowledge of the minuter, etc. In this work, we present the first of its kind dataset on Automatic Minuting. We develop a dataset of English and Czech technical project meetings, consisting of transcripts generated from ASRs, manually corrected, and minuted by several annotators. Our dataset, ELITR Minuting Corpus, consists of 120 English and 59 Czech meetings, covering about 180 hours of meeting content. The corpus is publicly available at http://hdl.handle.net/11234/1-4692 as a set of meeting transcripts and minutes, excluding the recordings for privacy reasons. A unique feature of our dataset is that most meetings are equipped with more than one minute, each created independently. Our corpus thus allows studying differences in what people find important while taking the minutes. We also provide baseline experiments for the community to explore this novel problem further. To the best of our knowledge, ELITR Minuting Corpus is probably the first resource on minuting in English and also in a language other than English (Czech).
KW - automatic minuting
KW - meeting summarization
KW - multi-party dialogues
UR - http://www.scopus.com/inward/record.url?scp=85130503150&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85130503150
T3 - 2022 Language Resources and Evaluation Conference, LREC 2022
SP - 3174
EP - 3182
BT - 2022 Language Resources and Evaluation Conference, LREC 2022
A2 - Calzolari, Nicoletta
A2 - Bechet, Frederic
A2 - Blache, Philippe
A2 - Choukri, Khalid
A2 - Cieri, Christopher
A2 - Declerck, Thierry
A2 - Goggi, Sara
A2 - Isahara, Hitoshi
A2 - Maegaard, Bente
A2 - Mariani, Joseph
A2 - Mazo, Helene
A2 - Odijk, Jan
A2 - Piperidis, Stelios
PB - European Language Resources Association (ELRA)
Y2 - 20 June 2022 through 25 June 2022
ER -