Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Nguyen, Tu Ahn"'
Autor:
Tomasello, Paden, Shrivastava, Akshat, Lazar, Daniel, Hsu, Po-Chun, Le, Duc, Sagar, Adithya, Elkahky, Ali, Copet, Jade, Hsu, Wei-Ning, Adi, Yossi, Algayres, Robin, Nguyen, Tu Ahn, Dupoux, Emmanuel, Zettlemoyer, Luke, Mohamed, Abdelrahman
End-to-end spoken language understanding (SLU) predicts intent directly from audio using a single model. It promises to improve the performance of assistant systems by leveraging acoustic information lost in the intermediate textual representation an
Externí odkaz:
http://arxiv.org/abs/2207.10643
Autor:
Nguyen, Tu-Ahn, Fyhn, Michael B.W., Kristensen, Jeppe Ågård, Nielsen, Lars Henrik, Thomsen, Tonny B., Keulen, Nynke, Lindström, Sofie, Boldreel, Lars O.
Publikováno v:
In Gondwana Research October 2021 98:166-190
Autor:
Tomasello, Paden, Shrivastava, Akshat, Lazar, Daniel, Hsu, Po-Chun, Le, Duc, Sagar, Adithya, Elkahky, Ali, Copet, Jade, Hsu, Wei-Ning, Adi, Yossi, Algayres, Robin, Nguyen, Tu Ahn, Dupoux, Emmanuel, Zettlemoyer, Luke, Mohamed, Abdelrahman
Publikováno v:
IEEE
SLT-2022-IEEE Spoken Language Technology Workshop
SLT-2022-IEEE Spoken Language Technology Workshop, Jan 2023, Doha, Qatar
SLT-2022-IEEE Spoken Language Technology Workshop
SLT-2022-IEEE Spoken Language Technology Workshop, Jan 2023, Doha, Qatar
End-to-end spoken language understanding (SLU) predicts intent directly from audio using a single model. It promises to improve the performance of assistant systems by leveraging acoustic information lost in the intermediate textual representation an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e85f45cfbdf744dbdf321b9de071a495
https://inria.hal.science/hal-03989829
https://inria.hal.science/hal-03989829