Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
LowResourceEval2021: a shared task on speech processing for lowresource languages. / Klyachko, Elena; Гребенкин, Даниил Витальевич; Носенко, Дарья Игоревна и др.
Computational Linguistics and Intellectual Technologies: Papers from the Annual International Conference “Dialogue” (2021). Том Выпуск 20 Москва : Российский государственный гуманитарный университет, 2021. 36.Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
}
TY - GEN
T1 - LowResourceEval2021: a shared task on speech processing for lowresource languages
AU - Klyachko, Elena
AU - Гребенкин, Даниил Витальевич
AU - Носенко, Дарья Игоревна
AU - Serikov, Oleg
N1 - Klyachko E., Grebenkin D., Nosenko D., Serikov O. LowResourceEval2021: a shared task on speech processing for lowresource languages // Computational Linguistics and Intellectual Technologies: Papers from the Annual International Conference “Dialogue” (2021), iss. 20.
PY - 2021
Y1 - 2021
N2 - This paper describes the results of the first shared task on speech processing for lowresource languages of Russia. Speech processing tasks are notoriously dataconsuming. The aim of the shared task was to evaluate the performance of stateoftheart models on lowresource language data as well as draw the attention of experts to field linguistics data (using Lingovodoc project data). The tasks included language identification and IPA transcription, with three teams participating in them. The paper also provides a description for the datasets as well as an analysis of the participants’ solutions. The datasets created as a result of the shared task can be used in other tasks to enhance speech processing and help develop modern NLP tools for both speech communities and field linguists.
AB - This paper describes the results of the first shared task on speech processing for lowresource languages of Russia. Speech processing tasks are notoriously dataconsuming. The aim of the shared task was to evaluate the performance of stateoftheart models on lowresource language data as well as draw the attention of experts to field linguistics data (using Lingovodoc project data). The tasks included language identification and IPA transcription, with three teams participating in them. The paper also provides a description for the datasets as well as an analysis of the participants’ solutions. The datasets created as a result of the shared task can be used in other tasks to enhance speech processing and help develop modern NLP tools for both speech communities and field linguists.
UR - https://www.dialog-21.ru/digest/2021/articles/
U2 - 10.28995/2075-7182-2021-20-391-402
DO - 10.28995/2075-7182-2021-20-391-402
M3 - Conference contribution
SN - 978-5-7281-3032-1
SN - 978-5-7281-3031-4
VL - Выпуск 20
BT - Computational Linguistics and Intellectual Technologies
PB - Российский государственный гуманитарный университет
CY - Москва
ER -
ID: 35270557