Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Kyosuke Nishida"'
Publikováno v:
NTT Technical Review. 19:23-30
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::98ee587ab28aac5bf17c0f547b676614
https://doi.org/10.53829/ntr202112fa2
https://doi.org/10.53829/ntr202112fa2
Publikováno v:
Interspeech 2022.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aac803c1eb3fd0edf951c00611d2c926
https://doi.org/10.21437/interspeech.2022-327
https://doi.org/10.21437/interspeech.2022-327
Publikováno v:
Acoustical Science and Technology. 42:1-11
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8abb41b2ed800c665331830e06acdac9
https://doi.org/10.1250/ast.42.1
https://doi.org/10.1250/ast.42.1
Publikováno v:
NTT Technical Review. 18:59-63
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4f087d1f5a565b3f0be6d97e69d48470
https://doi.org/10.53829/ntr202012fa9
https://doi.org/10.53829/ntr202012fa9
Publikováno v:
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::eb3f1cb7b88f844e5df00514711d13b5
https://doi.org/10.18653/v1/2022.acl-srw.34
https://doi.org/10.18653/v1/2022.acl-srw.34
Publikováno v:
2021 International Joint Conference on Neural Networks (IJCNN).
Multi-hop QA with annotated supporting facts, which is the task of reading comprehension (RC) considering the interpretability of the answer, has been extensively studied. In this study, we define an interpretable reading comprehension (IRC) model as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b342d6d249d0a4139da84bb54702403
https://doi.org/10.1109/ijcnn52387.2021.9534370
https://doi.org/10.1109/ijcnn52387.2021.9534370
Publikováno v:
ACL/IJCNLP (Findings)
Pre-trained language models (PTLMs) acquire domain-independent linguistic knowledge through pre-training with massive textual resources. Additional pre-training is effective in adapting PTLMs to domains that are not well covered by the pre-training c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1fb217307906bc6ccd85557ce7f91a15
Publikováno v:
INTERSPEECH
One of the problems with automated audio captioning (AAC) is the indeterminacy in word selection corresponding to the audio event/scene. Since one acoustic event/scene can be described with several words, it results in a combinatorial explosion of po
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1da1cc17a1f427f03fdff417f1983b6c
https://doi.org/10.21437/interspeech.2020-2087
https://doi.org/10.21437/interspeech.2020-2087
Publikováno v:
ASRU
This paper presents a generalized form of large-context language models (LCLMs) that can take linguistic contexts beyond utterance boundaries into consideration. In discourse-level and conversation-level automatic speech recognition (ASR) tasks, whic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a935f535cfb8118d665de8c47a84805a
https://doi.org/10.1109/asru46091.2019.9003857
https://doi.org/10.1109/asru46091.2019.9003857