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pro vyhledávání: '"Kim Seok-Min"'
We introduce EM-Network, a novel self-distillation approach that effectively leverages target information for supervised sequence-to-sequence (seq2seq) learning. In contrast to conventional methods, it is trained with oracle guidance, which is derive
Externí odkaz:
http://arxiv.org/abs/2306.10058
Self-supervised learning (SSL) has shown significant progress in speech processing tasks. However, despite the intrinsic randomness in the Transformer structure, such as dropout variants and layer-drop, improving the model-level consistency remains u
Externí odkaz:
http://arxiv.org/abs/2306.08463
Most speech-to-text (S2T) translation studies use English speech as a source, which makes it difficult for non-English speakers to take advantage of the S2T technologies. For some languages, this problem was tackled through corpus construction, but t
Externí odkaz:
http://arxiv.org/abs/2107.02875
Autor:
Lee, Dongjin, Kim, Seok Min, Kim, Dahong, Baek, Seung Yeop, Yeo, Seon Ju, Lee, Jae Jong, Cha, Chaenyung, Park, Su A, Kim, Tae-Don
Publikováno v:
In Materials Today Bio June 2024 26
Paraphrasing is often performed with less concern for controlled style conversion. Especially for questions and commands, style-variant paraphrasing can be crucial in tone and manner, which also matters with industrial applications such as dialog sys
Externí odkaz:
http://arxiv.org/abs/2103.13439
Modern dialog managers face the challenge of having to fulfill human-level conversational skills as part of common user expectations, including but not limited to discourse with no clear objective. Along with these requirements, agents are expected t
Externí odkaz:
http://arxiv.org/abs/1912.00342
Different from the writing systems of many Romance and Germanic languages, some languages or language families show complex conjunct forms in character composition. For such cases where the conjuncts consist of the components representing consonant(s
Externí odkaz:
http://arxiv.org/abs/1905.13656
Ethics regarding social bias has recently thrown striking issues in natural language processing. Especially for gender-related topics, the need for a system that reduces the model bias has grown in areas such as image captioning, content recommendati
Externí odkaz:
http://arxiv.org/abs/1905.11684
Autor:
Asgar, Md. Ali, Kim, Jun, Lee, Seongmin, Van Tran, Chau, Haq, Muhammad Refatul, In, Jung Bin, Kim, Seok-min
Publikováno v:
In Microchemical Journal June 2023 189
Akademický článek
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