Výsledky vyhledávání - "Tomoyosi Akiba"

English-Japanese Machine Translation for Lecture Subtitles using Back-Translation and Transfer Learning

Autor: Yuuki Yamagishi, Hajime Tsukada, Tomoyosi Akiba

Publikováno v: GCCE

In this study, we report our efforts to improve the performance of English-Japanese machine translation on the “Technology, Entertainment, Design (TED)” lecture data. We experimented with two methods to improve English-Japanese translation focusi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::be45f8b41d86b19575c33195f591e195
https://doi.org/10.1109/gcce50665.2020.9291882

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Multi-label Disease Classification of Patient's Tweets using Automatically Acquired Training Corpus

Autor: Tomohiro Okuda, Tomoyosi Akiba, Reine Asakawa

Publikováno v: 2020 7th International Conference on Advance Informatics: Concepts, Theory and Applications (ICAICTA).

Morbidity determination using tweet data is currently drawing huge attention within the field of influenza outbreak prediction. This work aims to develop a multi-label disease classification system targeting real tweets. One of the difficulties assoc

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::cdc837376b368900072c904f86f11880
https://doi.org/10.1109/icaicta49861.2020.9429057

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Using a Sequence-to-sequence Model for Large-scale Automated ICD Coding

Autor: Hiroki Hatanaka, Tomoyosi Akiba

Publikováno v: 2019 International Conference of Advanced Informatics: Concepts, Theory and Applications (ICAICTA).

In the domain of NLP (Natural Language Processing), there are studies on automated ICD coding from text data. Due to the sparsity of the training data, it is difficult to process codes that represent rare diseases. Therefore, in many previous studies

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2db3bfa864cf72fa2fde0555e5d24660
https://doi.org/10.1109/icaicta.2019.8904397

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Rapid Speaker Adaptation of Neural Network Based Filterbank Layer for Automatic Speech Recognition

Autor: Seiichi Nakagawa, Tomoyosi Akiba, Hiroshi Seki, Kazumasa Yamamoto

Publikováno v: SLT

Deep neural networks (DNN) have achieved significant success in the field of automatic speech recognition. Previously, we proposed a filterbank-incorporated DNN which takes power spectra as input features. This method has a function of VTLN (Vocal tr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::dc072e83ee72535059ac9389507f2803
https://doi.org/10.1109/slt.2018.8639648

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