no code implementations • FNP (LREC) 2022 • Gakuto Tsutsumi, Takehito Utsuro
As the first step towards developing such a system, this paper takes an approach of employing a BERT-based machine reading comprehension model, which extracts causes of stock price rise and decline from news reports on stock price changes.
no code implementations • 23 Sep 2022 • Yizhen Wei, Takehito Utsuro, Masaaki Nagata
Based on extended word alignment, we further propose a novel task called refined word-level QE that outputs refined tags and word-level correspondences.
1 code implementation • 3 Apr 2021 • Yu Wang, Chee Siang Leow, Akio Kobayashi, Takehito Utsuro, Hiromitsu Nishizaki
This paper describes the ExKaldi-RT online automatic speech recognition (ASR) toolkit that is implemented based on the Kaldi ASR toolkit and Python language.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • Asian Chapter of the Association for Computational Linguistics 2020 • Hongyu Li, Tengyang Chen, Shuting Bai, Takehito Utsuro, Yasuhide Kawada
Models developed for Machine Reading Comprehension (MRC) are asked to predict an answer from a question and its related context.
no code implementations • WS 2020 • Tengyang Chen, Hongyu Li, Miho Kasamatsu, Takehito Utsuro, Yasuhide Kawada
Considering such a situation within the field of the non-factoid QA, this paper aims to develop a dataset for training Japanese how-to tip QA models.
no code implementations • WS 2020 • Hongyi Cui, Yizhen Wei, Shohei Iida, Takehito Utsuro, Masaaki Nagata
In this paper, we introduce University of Tsukuba{'}s submission to the IWSLT20 Open Domain Translation Task.
no code implementations • LREC 2020 • Huaijin Deng, Youchao Lin, Takehito Utsuro, Akio Kobayashi, Hiromitsu Nishizaki, Junichi Hoshino
The experimental evaluation results of those integrated diverse features indicate that time sequential acoustic features contribute to improving the model with disfluency-based and prosodic features when detecting fluent speech, but not when detecting disfluent speech.
no code implementations • LREC 2020 • Youchao Lin, Miho Kasamatsu, Tengyang Chen, Takuya Fujita, Huanjin Deng, Takehito Utsuro
While playing the communication game {``}Are You a Werewolf{''}, a player always guesses other players{'} roles through discussions, based on his own role and other players{'} crucial utterances.
no code implementations • WS 2019 • Hongyi Cui, Shohei Iida, Po-Hsuan Hung, Takehito Utsuro, Masaaki Nagata
Recently, the Transformer becomes a state-of-the-art architecture in the filed of neural machine translation (NMT).
no code implementations • ACL 2019 • Shohei Iida, Ryuichiro Kimura, Hongyi Cui, Po-Hsuan Hung, Takehito Utsuro, Masaaki Nagata
The first hop attention is the scaled dot-product attention which is the same attention mechanism used in the original Transformer.
no code implementations • WS 2018 • Hayato Shiokawa, Kota Kawaguchi, Bingcai Han, Takehito Utsuro, Yasuhide Kawada, Masaharu Yoshioka, K, Noriko o
In order to improve the efficiency of using search engine for academic study, it is necessary to invent a technique of measuring the beginner friendliness of a Web page explaining academic concepts and to build an automatic measurement system.
no code implementations • WS 2017 • Zi Long, Ryuichiro Kimura, Takehito Utsuro, Tomoharu Mitsuhashi, Mikio Yamamoto
Long et al.(2017) proposed to select phrases that contain out-of-vocabulary words using the statistical approach of branching entropy.
no code implementations • WS 2016 • Zi Long, Takehito Utsuro, Tomoharu Mitsuhashi, Mikio Yamamoto
We train an NMT system on bilingual data wherein technical terms are replaced with technical term tokens; this allows it to translate most of the source sentences except technical terms.
no code implementations • MTSummit 2017 • Zi Long, Ryuichiro Kimura, Takehito Utsuro, Tomoharu Mitsuhashi, Mikio Yamamoto
Neural machine translation (NMT), a new approach to machine translation, has achieved promising results comparable to those of traditional approaches such as statistical machine translation (SMT).
no code implementations • LREC 2016 • Takakazu Imada, Yusuke Inoue, Lei Chen, Syunya Doi, Tian Nie, Chen Zhao, Takehito Utsuro, Yasuhide Kawada
We finally propose how to predict the market share of a specific product genre based on the rates of concerns of those who search for Web pages.
no code implementations • LREC 2012 • Takafumi Suzuki, Yusuke Abe, Itsuki Toyota, Takehito Utsuro, Suguru Matsuyoshi, Masatoshi Tsuchiya
In order to organize Japanese functional expressions with various surface forms, a lexicon of Japanese functional expressions with hierarchical organization was compiled.