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pro vyhledávání: '"Yogesh Virkar"'
Publikováno v:
Transactions of the Association for Computational Linguistics, Vol 11, Pp 419-435 (2023)
AbstractWe investigate how humans perform the task of dubbing video content from one language into another, leveraging a novel corpus of 319.57 hours of video from 54 professionally produced titles. This is the first such large-scale study we are awa
Externí odkaz:
https://doaj.org/article/7cd7c64a7ab346c5a7ac3360753a9343
Publikováno v:
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
We investigate how humans perform the task of dubbing video content from one language into another, leveraging a novel corpus of 319.57 hours of video from 54 professionally produced titles. This is the first such large-scale study we are aware of. T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6d646125d22d8d749783545bd5573eaa
Publikováno v:
ICASSP
Automatic dubbing is an extension of speech-to-speech translation such that the resulting target speech is carefully aligned in terms of duration, lip movements, timbre, emotion, prosody, etc. of the speaker in order to achieve audiovisual coherence.
Autor:
Robert Enyedi, Marcello Federico, Surafel Melaku Lakew, Yogesh Virkar, Cuong Hoang, Roberto Barra-Chicote, Yue Wang
Publikováno v:
ICASSP
Automatic dubbing aims at seamlessly replacing the speech in a video document with synthetic speech in a different language. The task implies many challenges, one of which is generating translations that not only convey the original content, but also
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2584428462de65bbad54bc54751635cb
Automatic dubbing (AD) is among the machine translation (MT) use cases where translations should match a given length to allow for synchronicity between source and target speech. For neural MT, generating translations of length close to the source le
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7fdb8568a01d501b77c539bbc1de6e8a
Publikováno v:
INTERSPEECH
Various functions of a network of excitable units can be enhanced if the network is in the `critical regime', where excitations are, on average, neither damped nor amplified. An important question is how can such networks self-organize to operate in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::007ef58fc1342a31f9e0ebf554717e0a
http://arxiv.org/abs/1802.02261
http://arxiv.org/abs/1802.02261
Publikováno v:
Physical review. E. 94(4-1)
Learning and memory are acquired through long-lasting changes in synapses. In the simplest models, such synaptic potentiation typically leads to runaway excitation, but in reality there must exist processes that robustly preserve overall stability of
Autor:
Yogesh Virkar, Aaron Clauset
Publikováno v:
Ann. Appl. Stat. 8, no. 1 (2014), 89-119
Many man-made and natural phenomena, including the intensity of earthquakes, population of cities and size of international wars, are believed to follow power-law distributions. The accurate identification of power-law patterns has significant conseq
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::57b684520952217326a8f8b1d668800b
http://projecteuclid.org/euclid.aoas/1396966280
http://projecteuclid.org/euclid.aoas/1396966280