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Shu Okabe

dblp:268/0912 · DBLP profile ↗
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4ranked-venue papers
2as first author
3since 2021 · last 2026
0009-0003-0169-3689ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 4 · 2 first-author · 3 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
3 papers
Speech recognition and synthesis · 50% Information extraction and text analysis · 29% Machine translation · 22%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational social science and digital humanities · 100%

Topics — the 3 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Speech recognition and synthesis › speech analysis
language identification
1.012026
CommonLID: Re-evaluating State-of-the-Art Language Identification Performance on Web Data · ACL (1) 2026
Natural language and speech › Information extraction and text analysis
word segmentation
0.612022
Weakly Supervised Word Segmentation for Computational Language Documentation · ACL (1) 2022
Natural language and speech › Machine translation › machine translation evaluation
translation quality estimation
0.412020
Multimodal Quality Estimation for Machine Translation · ACL 2020

Methods — techniques the papers use, named apart from their topics

weak supervision · 1.1incremental learning · 1.1bayesian nonparametric model · 1.1benchmark evaluation · 1.0
YearPublicationVenuePosition
2026 CommonLID: Re-evaluating State-of-the-Art Language Identification Performance on Web Data
abstract
Pedro Ortiz Suarez, Laurie Burchell, Catherine Arnett, Rafael Mosquera, Sara Hincapié Monsalve, Thom Vaughan, Damian Stewart, Malte Ostendorff, Idris Abdulmumin, Vukosi Marivate, Shamsuddeen Hassan Muhammad, Atnafu Lambebo Tonja, Hend Al-Khalifa, Nadia Ghezaiel Hammouda, Verrah Akinyi Otiende, Tack Hwa Wong, Jakhongir Saydaliev, Melika Nobakhtian, Muhammad Ravi Shulthan Habibi, Chalamalasetti Kranti, Carol Muchemi, Khang Nguyen, Faisal Muhammad Adam, Luis Frentzen Salim, Reem Alqifari, Cynthia Jayne Amol, Joseph Marvin Imperial, Ilker Kesen, Ahmad Mustafid, Pavel Stepachev, Leshem Choshen, David Anugraha, Hamada Nayel, Seid Muhie Yimam, Vallerie Alexandra Putra, My Chiffon Nguyen, Azmine Toushik Wasi, Gouthami Vadithya, Rob Van Der Goot, Lanwenn ar C’horr, Karan Dua, Andrew Yates, Mithil Bangera, Yeshil Bangera, Hitesh Laxmichand Patel, Shu Okabe, Fenal Ashokbhai Ilasariya, Dmitry Gaynullin, Genta Indra Winata, Yiyuan Li, Juan Pablo Martínez, Amit Agarwal, Ikhlasul Akmal Hanif, Raia Abu Ahmad, Esther Adenuga, Filbert Aurelian Tjiaranata, Weerayut Buaphet, Michael Anugraha, Sowmya Vajjala, Benjamin L Rice, Azril Hafizi Amirudin, Jesujoba Oluwadara Alabi, Srikant Panda, Yassine Toughrai, Bruhan Kyomuhendo, Daniel Ruffinelli, Akshata, Manuel Goulão, Ej Zhou, Ingrid Gabriela Franco Ramirez, Cristina Aggazzotti, Konstantin Dobler, Jun Kevin, Quentin Pagès, Nicholas Andrews, Nuhu Ibrahim, Mattes Ruckdeschel, Amr Keleg, Mike Zhang, Casper Rufaro Muziri, Saron Samuel, Sotaro Takeshita, Kun Kerdthaisong, Luca Foppiano, Rasul Dent, Tommaso Green, Ahmad Mustapha Wali, Kamohelo Makaaka, Vicky Feliren, Inshirah Idris, Hande Celikkanat, Abdulhamid Abubakar, Jean Maillard, Benoît Sagot, Thibault Clérice, Kenton Murray, Sarah K. K. Luger. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026.
Pedro Ortiz Suarez, Laurie Burchell, Catherine Arnett, Rafael Mosquera, Sara Hincapié Monsalve, Thom Vaughan, Damian Stewart, Malte Ostendorff, Idris Abdulmumin, Vukosi Marivate, Shamsuddeen Hassan Muhammad, Atnafu Lambebo Tonja, Hend Al-Khalifa 0001, Nadia Ghezaiel Hammouda, Verrah Otiende, Tack Hwa Wong, Jakhongir Saydaliev, Melika Nobakhtian, Muhammad Ravi Shulthan Habibi, Kranti Chalamalasetti, Carol Muchemi, Faisal Muhammad Adam, Luis Frentzen Salim, Reem Alqifari, Cynthia Jayne Amol, Joseph Marvin Imperial, Ilker Kesen, Ahmad Mustafid, Pavel Stepachev, Leshem Choshen, David Anugraha, Hamada A. Nayel, Seid Muhie Yimam, Vallerie Alexandra Putra, My Chiffon Nguyen, Azmine Toushik Wasi, Gouthami Vadithya, Rob van der Goot, Lanwenn Ar C'horr, Karan Dua, Andrew Yates, Mithil Bangera, Yeshil Bangera, Hitesh Laxmichand Patel, Shu Okabe, Fenal Ashokbhai Ilasariya, Dmitry Gaynullin, Genta Indra Winata, Yiyuan Li, Ikhlasul Akmal Hanif, Raia Abu Ahmad, Esther Adenuga, Filbert Aurelian Tjiaranata, Weerayut Buaphet, Michael Anugraha, Sowmya Vajjala, Benjamin Rice, Azril Hafizi Amirudin, Jesujoba O. Alabi, Srikant Panda, Yassine Toughrai, Bruhan Kyomuhendo, Daniel Ruffinelli, Akshata A, Manuel Goulão, Ej Zhou, Ingrid Gabriela Franco Ramirez, Cristina Aggazzotti, Konstantin Dobler, Jun Kevin, Quentin Pagès, Nicholas Andrews, Nuhu Ibrahim, Mattes Ruckdeschel, Amr Keleg, Mike Zhang, Casper Muziri, Saron Samuel, Sotaro Takeshita, Kun Kerdthaisong, Luca Foppiano, Rasul Dent, Tommaso Green, Ahmad Mustapha Wali, Kamohelo Makaaka, Vicky Feliren, Inshirah Idris, Hande Çelikkanat, Abdulhamid Abubakar, Jean Maillard, Benoît Sagot, Thibault Clérice, Kenton Murray, Sarah K. K. Luger
ACL (1)46
2026 Parallel Sentence Filtering for Low-Resource Language Pairs: A Case Study for Upper Sorbian, German, and Czech
Ruiyang Jiang, Shu Okabe, Alexander Fraser 0001
LREC2
2022 Weakly Supervised Word Segmentation for Computational Language Documentation
abstract
Word and morpheme segmentation are fundamental steps of language documentation as they allow to discover lexical units in a language for which the lexicon is unknown.However, in most language documentation scenarios, linguists do not start from a blank page: they may already have a pre-existing dictionary or have initiated manual segmentation of a small part of their data.This paper studies how such a weak supervision can be taken advantage of in Bayesian non-parametric models of segmentation.Our experiments on two very low resource languages (Mboshi and Japhug), whose documentation is still in progress, show that weak supervision can be beneficial to the segmentation quality.In addition, we investigate an incremental learning scenario where manual segmentations are provided in a sequential manner.This work opens the way for interactive annotation tools for documentary linguists.
Shu Okabe, Laurent Besacier, François Yvon
ACL (1)1
2020 Multimodal Quality Estimation for Machine Translation
abstract
© 2020 The Authors. Published by Association for Computational Linguistics. This is an open access article available under a Creative Commons licence. \nThe published version can be accessed at the following link on the publisher’s website: http://dx.doi.org/10.18653/v1/2020.acl-main.114
Shu Okabe, Frédéric Blain, Lucia Specia
ACL1