David Ifeoluwa Adelani

Biography

David Adelani is an assistant professor at McGill University’s School of Computer Science under the Fighting Inequities initiative, and a core academic member of Mila – Quebec Artificial Intelligence Institute.

Adelani’s research focuses on multilingual natural language processing with special attention to under-resourced languages.

Current Students

Henok Ademtew

Master's Research - McGill University

Master's Research - McGill University

Virginia Ceccatelli

Collaborating researcher - McGill University

David Guzmán Ramírez

PhD - McGill University

Research Intern - McGill University

Research Intern - McGill University

Yejin Jeon

Postdoctorate - McGill University

Senyu Li Li

PhD - McGill University

Yinhan Lu

Collaborating researcher - McGill University

Marie Maltais

PhD - McGill University

Damaris Stephanie NDJEBAYI

PhD - McGill University

Juhyun Oh

Collaborating Alumni - McGill University

Jessica Ojo

Master's Research - McGill University

Research Intern - McGill University

Vivek Verma

Professional Master's - Université de Montréal

Jessica Wang

Research Intern - McGill University

Tianyou Xie

Research Intern - McGill University

Tianyi Xu Xu

Research Intern - McGill University

Peter Yu

Collaborating Alumni - McGill University

Publications

WorldCuisines: A Massive-Scale Benchmark for Multilingual and Multicultural Visual Question Answering on Global Cuisines

Genta Indra Winata

Frederikus Hudi

Patrick Amadeus Irawan

David Anugraha

Rifki Afina Putri

Yutong Wang

Adam Nohejl

Ubaidillah Ariq Prathama

Nedjma OUSIDHOUM

Afifa Amriani

Anar Rzayev

Anirban Das

Ashmari Pramodya

Aulia Adila

Bryan Wilie

Candy Olivia Mawalim

Ching Lam Cheng

Daud Abolade

Emmanuele Chersoni

Enrico Santus … (see 31 more)

Fariz Ikhwantri

Garry Kuwanto

Hanyang Zhao

Haryo Akbarianto Wibowo

Holy Lovenia

Jan Christian Blaise Cruz

Jan Wira Gotama Putra

Junho Myung

Lucky Susanto

Maria Angelica Riera Machin

Marina Zhukova

Michael Anugraha

Muhammad Farid Adilazuarda

Natasha Santosa

Peerat Limkonchotiwat

Raj Dabre

Rio Alexander Audino

Samuel Cahyawijaya

Shi-Xiong Zhang

Stephanie Yulia Salim

Yi Zhou

Yinxuan Gui

En-Shiun Annie Lee

Shogo Okada

Ayu Purwarianti

Alham Fikri Aji

Taro Watanabe

Derry Tanti Wijaya

Alice Oh

Chong-Wah Ngo

2024-10-15

ArXiv (preprint)

CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark

David LE MEUR

David Orlando Romero Mogrovejo

Chenyang Lyu

Haryo Akbarianto Wibowo

Teresa Lynn

Injy Hamed

Aditya Nanda Kishore Khandavally

Aishik Mandal

Alina Dragonetti

Artem Abzaliev

Atnafu Lambebo Tonja

Bontu Fufa Balcha

Chenxi Whitehouse

Christian Salamea-Palacios

Dan John Velasco

D. Meur

Emilio Villa Cueva

Fajri Koto

Fauzan Farooqui … (see 57 more)

Frederico Belcavello

Ganzorig Batnasan

Gisela Vallejo

Gráinne Caulfield

Guido Ivetta

Haiyue Song

Henok Biadglign Ademtew

Hernán Maina

Holy Lovenia

Israel Abebe Azime

Jan Christian Blaise Cruz

Jay Gala

Jiahui Geng

Jesus-German Ortiz-Barajas

Jinheon Baek

Jocelyn Dunstan

Laura Alonso Alemany

Teresa Clifford

Kumaranage Ravindu Yasas Nagasinghe

Luciana Benotti

Luis Fernando D'Haro

Marcelo Viridiano

Marcos Estecha-Garitagoitia

Maria Camila Buitrago Cabrera

Mario Rodríguez-Cantelar

Mélanie Jouitteau

Mihail Minkov Mihaylov

Mohamed Fazli Mohamed Imam

Muhammad Farid Adilazuarda

Munkhjargal Gochoo

Munkh-Erdene Otgonbold

Naome Etori

Olivier NIYOMUGISHA

Paula Mónica Silva

Pranjal A Chitale

Raj Dabre

Rendi Chevi

Ruochen Zhang

Ryandito Diandaru

Samuel Cahyawijaya

Santiago Góngora

Soyeong Jeong

Sukannya Purkayastha

Tatsuki Kuribayashi

Thanmay Jayakumar

Tiago Timponi Torrent

Toqeer Ehsan

Vladimir Araujo

Yova Kementchedjhieva

Zara Burzo

Zheng Wei Lim

Zheng Xin Yong

Oana Ignat

Joan Nwatu

Rada Mihalcea

Thamar Solorio

Alham Fikri Aji

2024-09-25

NeurIPS.cc/2024/Datasets_and_Benchmarks_Track (oral)

openreview.net

MINERS: Multilingual Language Models as Semantic Retrievers

Genta Indra Winata

Ruochen Zhang

Words have been represented in a high-dimensional vector space that encodes their semantic similarities, enabling downstream applications su… (see more)ch as retrieving synonyms, antonyms, and relevant contexts. However, despite recent advances in multilingual language models (LMs), the effectiveness of these models' representations in semantic retrieval contexts has not been comprehensively explored. To fill this gap, this paper introduces the MINERS, a benchmark designed to evaluate the ability of multilingual LMs in semantic retrieval tasks, including bitext mining and classification via retrieval-augmented contexts. We create a comprehensive framework to assess the robustness of LMs in retrieving samples across over 200 diverse languages, including extremely low-resource languages in challenging cross-lingual and code-switching settings. Our results demonstrate that by solely retrieving semantically similar embeddings yields performance competitive with state-of-the-art approaches, without requiring any fine-tuning.

2024-06-10

ArXiv (preprint)

IrokoBench: A New Benchmark for African Languages in the Age of Large Language Models

Jessica Ojo

Israel Abebe Azime

Zhuang Yun Jian

Jesujoba Oluwadara Alabi

Xuanli He

Millicent Ochieng

Sara Hooker

Andiswa Bukula

En-Shiun Annie Lee

Chiamaka Ijeoma Chukwuneke

Happy Buzaaba

Blessing Kudzaishe Sibanda

Godson Kalipe

Jonathan Mukiibi

Salomon Kabongo

Foutse Yuehgoh

M. Setaka

Lolwethu Ndolela

Nkiruka Bridget Odu … (see 6 more)

Rooweither Mabuya

Shamsuddeen Hassan Muhammad

Salomey Osei

Sokhar Samb

Tadesse Kebede Guge

Pontus Stenetorp

Despite the widespread adoption of Large language models (LLMs), their remarkable capabilities remain limited to a few high-resource languag… (see more)es. Additionally, many low-resource languages (e.g. African languages) are often evaluated only on basic text classification tasks due to the lack of appropriate or comprehensive benchmarks outside of high-resource languages. In this paper, we introduce IrokoBench -- a human-translated benchmark dataset for 16 typologically-diverse low-resource African languages covering three tasks: natural language inference~(AfriXNLI), mathematical reasoning~(AfriMGSM), and multi-choice knowledge-based QA~(AfriMMLU). We use IrokoBench to evaluate zero-shot, few-shot, and translate-test settings~(where test sets are translated into English) across 10 open and four proprietary LLMs. Our evaluation reveals a significant performance gap between high-resource languages~(such as English and French) and low-resource African languages. We observe a significant performance gap between open and proprietary models, with the highest performing open model, Aya-101 only at 58\% of the best-performing proprietary model GPT-4o performance. Machine translating the test set to English before evaluation helped to close the gap for larger models that are English-centric, like LLaMa 3 70B. These findings suggest that more efforts are needed to develop and adapt LLMs for African languages.

2024-06-04

ArXiv (preprint)

AfriMTE and AfriCOMET: Enhancing COMET to Embrace Under-resourced African Languages

Jiayi Wang

Sweta Agrawal

Marek Masiak

Ricardo Rei

Eleftheria Briakou

Marine Carpuat

Xuanli He

Sofia Bourhim

Andiswa Bukula

Muhidin A. Mohamed

Temitayo Olatoye

Tosin Adewumi

Hamam Mokayed

Christine Mwase

Wangui Kimotho

Foutse Yuehgoh

Aremu Anuoluwapo

Jessica Ojo

Shamsuddeen Hassan Muhammad … (see 41 more)

Salomey Osei

Abdul-Hakeem Omotayo

Chiamaka Ijeoma Chukwuneke

Perez Ogayo

Oumaima Hourrane

Salma El Anigri

Lolwethu Ndolela

Thabiso Mangwana

Shafie Abdi Mohamed

Hassan Ayinde

Ayinde Hassan

Oluwabusayo Olufunke Awoyomi

Lama Alkhaled

sana Sabah al-azzawi

Naome Etori

Millicent Ochieng

Clemencia Siro

Samuel Njoroge

Njoroge Kiragu

Eric Muchiri

Wangari Kimotho

Lyse Naomi Wamba

Daud Abolade

Simbiat Ajao

Iyanuoluwa Shode

Ricky Macharm

Ruqayya Nasir Iro

Saheed Salahudeen Abdullahi

Stephen Moore

Bernard Opoku

Zainab Akinjobi

Abeeb Afolabi

Nnaemeka Casmir Obiefuna

Onyekachi Ogbu

Sam Brian

Sam Ochieng’

Verrah Akinyi Otiende

CHINEDU EMMANUEL MBONU

Toadoum Sari Sakayo

Yao Lu

Pontus Stenetorp

Despite the recent progress on scaling multilingual machine translation (MT) to several under-resourced African languages, accurately measur… (see more)ing this progress remains challenging, since evaluation is often performed on n-gram matching metrics such as BLEU, which typically show a weaker correlation with human judgments. Learned metrics such as COMET have higher correlation; however, the lack of evaluation data with human ratings for under-resourced languages, complexity of annotation guidelines like Multidimensional Quality Metrics (MQM), and limited language coverage of multilingual encoders have hampered their applicability to African languages. In this paper, we address these challenges by creating high-quality human evaluation data with simplified MQM guidelines for error detection and direct assessment (DA) scoring for 13 typologically diverse African languages. Furthermore, we develop AfriCOMET: COMET evaluation metrics for African languages by leveraging DA data from well-resourced languages and an African-centric multilingual encoder (AfroXLM-R) to create the state-of-the-art MT evaluation metrics for African languages with respect to Spearman-rank correlation with human judgments (0.441).

2024-05-31

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) (published)

Comparing LLM prompting with Cross-lingual transfer performance on Indigenous and Low-resource Brazilian Languages

A. Seza Doğruöz

Andr'e Coneglian

Atul Kr. Ojha

Large Language Models are transforming NLP for a variety of tasks. However, how LLMs perform NLP tasks for low-resource languages (LRLs) is … (see more)less explored. In line with the goals of the AmericasNLP workshop, we focus on 12 LRLs from Brazil, 2 LRLs from Africa and 2 high-resource languages (HRLs) (e.g., English and Brazilian Portuguese). Our results indicate that the LLMs perform worse for the part of speech (POS) labeling of LRLs in comparison to HRLs. We explain the reasons behind this failure and provide an error analysis through examples observed in our data set.

2024-04-27

ArXiv (preprint)

EkoHate: Abusive Language and Hate Speech Detection for Code-switched Political Discussions on Nigerian Twitter

Comfort Eseohen Ilevbare

Jesujoba Oluwadara Alabi

Firdous Damilola Bakare

Oluwatoyin Bunmi Abiola

Oluwaseyi A. Adeyemo

Nigerians have a notable online presence and actively discuss political and topical matters. This was particularly evident throughout the 20… (see more)23 general election, where Twitter was used for campaigning, fact-checking and verification, and even positive and negative discourse. However, little or none has been done in the detection of abusive language and hate speech in Nigeria. In this paper, we curated code-switched Twitter data directed at three musketeers of the governorship election on the most populous and economically vibrant state in Nigeria; Lagos state, with the view to detect offensive speech in political discussions. We developed EkoHate -- an abusive language and hate speech dataset for political discussions between the three candidates and their followers using a binary (normal vs offensive) and fine-grained four-label annotation scheme. We analysed our dataset and provided an empirical evaluation of state-of-the-art methods across both supervised and cross-lingual transfer learning settings. In the supervised setting, our evaluation results in both binary and four-label annotation schemes show that we can achieve 95.1 and 70.3 F1 points respectively. Furthermore, we show that our dataset adequately transfers very well to three publicly available offensive datasets (OLID, HateUS2020, and FountaHate), generalizing to political discussions in other regions like the US.

2024-04-27

ArXiv (preprint)

Are LLMs Breaking MT Metrics? Results of the WMT24 Metrics Shared Task

Markus Freitag

Nitika Mathur

Daniel Deutsch

Chi-kiu Lo

Eleftherios Avramidis

Ricardo Rei

Brian Thompson

Frédéric Blain

Tom Kocmi

Jiayi Wang

Marianna Buchicchio

Chrysoula Zerva

2023-12-31

Conference on Machine Translation (published)

Evaluating WMT 2024 Metrics Shared Task Submissions on AfriMTE (the African Challenge Set)

Jiayi Wang

Pontus Stenetorp

2023-12-31

Conference on Machine Translation (published)

Findings of the 2nd Shared Task on Multi-lingual Multi-task Information Retrieval at MRL 2024

Francesco Tinner

Raghav Mantri

Mammad Hajili

Chiamaka Ijeoma Chukwuneke

Dylan Massey

Benjamin A. Ajibade

Bilge Kocak

Abolade Dawud

Jonathan Atala

Hale Sirin

Kayode Olaleye

Anar Rzayev

Duygu Ataman

Large language models (LLMs) demonstrate exceptional proficiency in both the comprehension and generation of textual data, particularly in E… (see more)nglish, a language for which extensive public benchmarks have been established across a wide range of natural language processing (NLP) tasks. Nonetheless, their performance in multilingual contexts and specialized domains remains less rigorously validated, raising questions about their reliability and generalizability across linguistically diverse and domain-specific settings. The second edition of the Shared Task on Multilingual Multitask Information Retrieval aims to provide a comprehensive and inclusive multilingual evaluation benchmark which aids assessing the ability of multilingual LLMs to capture logical, factual, or causal relationships within lengthy text contexts and generate language under sparse settings, particularly in scenarios with under-resourced languages. The shared task consists of two subtasks crucial to information retrieval: Named entity recognition (NER) and reading comprehension (RC), in 7 data-scarce languages: Azerbaijani, Swiss German, Turkish and , which previously lacked annotated resources in information retrieval tasks. This year specifally focus on the multiple-choice question answering evaluation setting which provides a more objective setting for comparing different methods across languages.

2023-12-31

MRL (published)

Findings of the Association for Computational Linguistics: NAACL 2024, Mexico City, Mexico, June 16-21, 2024

Mohamed Abdalla

Gavin Abercrombie

Rodrigo Agerri

Zeljko Agic

Eneko Agirre

Monica Agrawal

Wasi Uddin Ahmad

James Allan

Aijun An

Antonios Anasta-sopoulos

Mark Anderson

Jacob Andreas

Marianna Apidianaki

Alessio Palmero

Yuki Aprosio

Ehsaneddin Arase

Giuseppe Asgari

Wilker Attardi

Aziz JinYeong … (see 480 more)

Timothy Bak

Mohamad Hardyman Baldwin

Pierpaolo Barawi

Ali Basile

Ja-smijn Basirat

Timo Bastings

Gábor Baumann

Eyal Bella

Farah Ben-David

Luciana Benamara

Benotti Yevgeni

Brijesh Berzak

Federico Bhatt

Chris Bianchi

Lidong Biemann

Alexandra Bing

Birch Eduardo

Gemma Blanco

Aurélien Boleda

Florian Bossard

Leonid Boudin

Ronan Boytsov

Pavel Le Bras

Chris Braslavski

Eleftheria Brew

Thomas Briakou

Emanuele Brochhagen

Wray Buglia-rello

Buntine Elena

Aoife Cabrio

Ruken Cahill

Jose Cakici

Marie Camacho-Collados

Pengfei Candito

Ziqiang Cao

Dallas Cao

Paula Card

Tommaso Carvalho

Andrew Caselli

Tanmoy Cattle

Ilias Chakrabor-ty

Angel X Chalkidis

Ching-Yun Chang

Snigdha Chang

Chen Chaturvedi

Kehai Chen

Long Chen

Lu Chen

Muhao Chen

Wei Chen

Wenhu Chen

Wenliang Chen

Xiang Chen

Yidong Chen

Yun-Nung Chen

Zhiyu Chen

Zhuang Chen

Hao Chen

Yu Cheng

Colin Cheng

Cherry Hai

Eunsol Leong Chieu

Leshem Choi

Monojit Choshen

Christos Choudhury

Yi-Ling Christodoulopou-los

Stephen Chung

Vincent Clark

Simone Claveau

John M Conia

Caio Filippo Conroy

Mathias Corro

Leyang Creutz

Aron Cui

Anna E Culotta

Amanda Cercas Currey

Curry Raj

Daniel Dabre

Cristian Dakota

Verna Danescu-Niculescu-Mizil

Budhaditya Dankers

Deb Vera

Zhenyun Demberg

Li Deng

Ruihai Dong

Antoine Dong

Eduard Doucet

Nan Dragut

Kevin Duan

Greg Duh

Ondrej Durrett

Tomasz Dusek

Dwojak Julian Martin

Asif Eisenschlos

Yanai Ekbal

Cristina Elazar

Luis España-Bonet

Espinosa-Anke Allyson

Kilian Ettinger

Evang Alexander

Agnieszka Fabbri

Meng Falenska

Marcello Fang

Hao Federico

Anna Fei

Feldman Naomi

Fuli Feldman

Xiaocheng Feng

Yansong Feng

Eric Feng

Francis Le Ferrand

Eli-sabetta Ferraro

Simone Fersini

Mark Filice

Mark Finlayson

Jennifer Fishel

Annemarie Foster

Friedrich Matthias

Zhe Gallé

Siddhant Gan

Judith Garg

Kallirroi Gaspers

Alborz Georgila

Geramifard Luke

Mor Gessler

Abbas Geva

Sahar Ghaddar

Filip Ghannay

Mario Ginter

Tejas Giulianelli

Sharon Gokhale

Rob Goldwater

Kyle van der Goot

Tanya Gorman

Jia-Chen Goyal

Qing-Wei Gu

Frank Gu

Lin Guerin

Honglei Gui

Qipeng Guo

Vivek Guo

Gupta Thanh-Le

Nizar Ha

Ivan Habash

Barry Habernal

Xianpei Haddow

Daniel Han

Peter Hardt

Di Hase

Michael He

Behnam Heck

Peter Hedayatnia

Daniel Heeman

Jack Hershcovich

Ryuichiro Hes-sel

Julia Higashinaka

Enamul Hockenmaier

Andreas Hoque

Yufang Hotho

Hou Dirk

Kristen Hovy

Di Howell

Xuming Hu

Fei Hu

Jie Huang

Lifu Huang

Peijie Huang

Shaohan Huang

Shujian Huang

Xuanjing Huang

Zhenzhen Huang

Mika Huang

Hämäläinen Kentaro

Inui Kokil

Hyeju Jaidka

Mustafa Jang

Yangfeng Jarrar

Lifeng Ji

Mali Jin

Qin Jin

Richard Jin

David Johansson

Preethi Jurgens

Jyothi Ehsan

Diptesh Kamalloo

S. Kanojia

Sarvnaz Kar

Pei Karimi

Daniel Ke

So-pan Khashabi

Tushar Khosla

Hyounghun Khot

Jin-Dong Kim

Joo-Kyung Kim

Taeuk Kim

Kim Roman

Rebecca Klinger

Ivan Knowles

Ekaterina Kobyzev

Philipp Kochmar

Koehn Mamoru

Rik Komachi

Lingpeng Koncel-Kedziorski

Julia Kong

Amrith Kreutzer

Kal-pesh Krishna

Udo Krishna

Artur Kruschwitz

Adhiguna Kulmizev

Kuncoro Wai

Gerasimos Lam

Mirella Lampouras

Staffan Lapata

Mark Larsson

Ivano Last

Lauriola Thu

Dong-Ho Le

Hwanhee Lee

Jinhyuk Lee

Mark G Lee

SangKeun Lee

Oliver Lee

Heather Le-mon

Piyawat Lent

Gina-Anne Lertvittayakumjorn

Miryam Levow

Bing de Lhoneux

Chuyuan Li

Dong Li

Jing Li

Junhui Li

Juntao Li

Li Li

Peng Li

Piji Li

Sujian Li

Li Tao

Wenjie Li

Xin Li

Yongbin Li

Yu Li

Yufei Li

Zhifei Li

Constantine Li

Chenghua Lignos

Hongyu Lin

Robert Lin

Bing Litschko

H. Liu

Kang Liu

Ming Liu

Qianying Liu

Tin-gwen Liu

Xuebo Liu

Yang Liu

Zhiyuan Liu

Zoey Liu

Ximing Liu

Anh Tuan Lu

Luu Chenyang

Lyu Ji

Jing Ma

Ruotian Ma

Xiaojuan Ma

Aman Ma

Harish Tayyar Madaan

Andrea Madabushi

Navonil Ma-dotto

Prodromos Majumder

Shervin Malakasiotis

Yuning Malmasi

Kelly Mao

Vukosi Marchi-sio

Stella Marivate

Lara J Markantonatou

Bruno Martin

Yuval Martins

Sérgio Marton

Yuji Matos

Julian Matsumoto

Bryan McAuley

Ryan McCann

Kathleen McDonald

McKeown Mahnoosh

Yuxian Mehrabani

Samuel Meng

Timothee Mensah

Margot Mickus

Simon Mieskes

Yasuhide Mille

Makoto Miura

Daichi Miwa

David R Mochihashi

Lili Mortensen

Kha-lil Mou

Benjamin Mrini

Philippe Muller

Smaranda Muller

Rudra Muresan

Thomas Murthy

Müller Max

Müller-Eberstein Maria

Nona Nadejde

Mikio Naderi

Hideki Nakano

Linyong Nakayama

Nan

Franco Maria

Tapas Nardini

Mark-Jan Nayak

Isar Nederhof

Mariana Nejadgholi

Dat Quoc Neves

Nguyen Le-Minh

Thien Huu Nguyen

Vahid Nguyen

Partovi Nia

Jan Niehues

Qiang Ning

Maciej Ogrodniczuk

Alice Oh

Naoaki Okazaki

Manabu Okumura

Matan Orbach

Nedjma Ou-sidhoum

Vasile Pais

Nikolaos Pappas

Joonsuk Park

Yannick Parmentier

Prasannan Parthasarathi

Lucia Passaro

Ramakanth Pasunuru

Siddharth Patwardhan

Hao Peng

Lis Pereira

Laura Perez-Beltrachini

Maxime Peyrard

Jonas Pfeiffer

Bryan A. Plummer

Maja Popovic

Soujanya Poria

Daniel Preotiuc-Pietro

Emily Prud'hommeaux

Vikram Pudi

Peng Qian

Tieyun Qian

Deepak Ramachandran

Carlos Ramisch

Leonardo Ranaldi

Sudha Rao

Shauli Ravfogel

Marek Rei

Leonardo F. R. Ribeiro

Oleg Rokhlenko

Salvatore Romeo

Joseph Le Roux

Alla Rozov-skaya

Terry Ruas

Raphael Rubino

Ivan Vladimir Meza Ruiz

Maria Ryskina

Hassan Sajjad

Shubhra Kanti

Karmaker Santu

Maarten Sap

Naomi Saphra

Asad B. Sayeed

Dominik Schlechtweg

Viktor Schlegel

Natalie Schluter

Nathan Schneider

Hinrich Schuetze

H. Schwartz

Jingbo Shang

Vasu Sharma

Tianze Shi

Mohammad Shoeybi

Lei Shu

Melanie Siegel Maneesh

Kumar Singh

Pranaydeep Singh

Sunayana Sitaram

Kevin Small

Luca Soldaini

Aina Garí Soler

Wei Song

Xingyi Song

Yan Song

Jeffrey S. Sorensen

Aitor Soroa

Jacopo Staiano

Efstathios Stamatatos

Gabriel Stanovsky

Shane Steinert-Threlkeld

Jannik Strötgen

Sara Stymne

Jinsong Su

Saku Sugawara

Alessandro Suglia

Aixin Sun

Cheng-jie Sun

Kai Sun

György Szarvas

Víctor M. Sánchez-Cartagena

Gözde Gül ¸Sahin

Zeerak Talat

Chenhao Tan

Hao Tan

Tianyi Tang

Jesse Thomason

Brian Thompson

Yuanhe Tian

Zhiliang Tian

Amalia Todirascu

Sara Tonelli

Paolo Torroni

Kristina Toutanova

Amine xv Trabelsi

Trang Tran

David R. Traum

Kewei Tu

Martin Tutek

Ana Sabina Uban

Takehito Utsuro

Olga Vechtomova

Yannick Versley

Karin M. Verspoor

David Vilar

David Vilares 0001

Serena Villa-ta

Esaú Villatoro-Tello

Thuy Vu

Ivan Vuli´c

Fei Xia

Tong Xiao

Bo Xu

Huijuan Xu

Nianwen Xue

S. Yadav

Hang Yan

Rui Yan

Min Yang

Wei Yang

Yezhou Yang

Yi Yang

Zhenglu Yang

Jin-Ge Yao

Wei Ye

Yongjing Yin

Naoki Yoshinaga

Koichiro Yoshino

Jianfei Yu

Juntao Yu Mo

Yu Manzil Zaheer

Fabio Massimo Zanzotto

Weixin Zeng

Luke Zettlemoyer

Biao Zhang

Chen Zhang

Crystina Zhang

Jiajun Zhang

Jingyi Zhang

Justine Zhang

Meishan Zhang

Ningyu Zhang

Shaolei Zhang

Sheng Zhang

Shiyue Zhang

Shuai Zhang

Shuo Zhang

Wei Zhang

Yang Zhang

Zhe Zhang

Jieyu Zhao

Shiwan Zhao

Hai-Tao Zheng

Zaixiang Zheng

Jie Zhou

Yi Zhou

Xiaodan Zhu

2023-12-31

NAACL-HLT (Findings) (published)

dblp.uni-trier.de

ÌròyìnSpeech: A multi-purpose Yorùbá Speech Corpus

Tolúlope' Ògúnremí

Kọ́lá Túbọ̀sún

Aremu Anuoluwapo

Iroro Orife

2023-12-31

LREC/COLING (published)