ACM Transactions on

Asian and Low-Resource Language Information Processing (TALLIP)

Latest Articles

Chinese Open Relation Extraction and Knowledge Base Establishment

Arabic Speech Act Recognition Techniques

Application of Structural and Topological Features to Recognize Online Handwritten Bangla Characters

Incorporating Prior Knowledge into Word Embedding for Chinese Word Similarity Measurement

Learning to Recommend Related Entities With Serendipity for Web Search Users


Science Citation Index Listing

TALLIP will be listed in the Science Citation Index Expanded starting with the first 2015 issue, 14(1). TALLIP will be included in the 2017 Journal Citation Report, and the first Impact Factor will be published mid-2018.

New Name, Expanded Scope

This page provides information about the journal Transactions on Asian and Low-Resource Language Information Processing (TALLIP), a publication of the Association for Computing Machinery (ACM).

The journal was formerly known as the Transactions on Asian Language Information Processing (TALIP): see the editorial charter for information on the expanded scope of the journal.  

A Dependency Parser for Spontaneous Chinese Spoken Language

Novel Character Identification Utilizing Semantic Relation with Animate Nouns in Korean

For identifying speakers of quoted speech or extracting social networks from literature, it is indispensable to extract character names and nominals. However, detecting proper nouns in the novels translated into or written in Korean is harder than in English because Korean does not have capitalization feature. In addition, it is almost impossible for any proper noun dictionary to include all kind of character names which have been created or will be created by authors. Fortunately, a previous study shows that utilizing postpositions for animate nouns is a simple and effective tool for character identification in Korean novels without a proper noun dictionary and a training corpus. In this paper, we propose a character identification method utilizing the semantic relation with known animate nouns. For 80 novels in Korean, the proposed method increases the micro- and macro-average recall by 13.68% and 11.86%, respectively, while decreasing the micro-average precision by 0.28% and increasing the macro-average precision by 0.07% compared to the previous study. If we focus on characters that are responsible for more than 1% of the character name mentions in each novel, the micro- and macro-average F-measure of the proposed method are 96.98% and 97.32%, respectively.

The Rule-Based Sundanese Stemmer

Our research proposed an iterative Sundanese stemmer by removing the derivational affixes prior to the inflexional. This scheme was chosen because, in the Sundanese affixation, a confix (one of derivational affix) is applied in the last phase of a morphological process. Moreover, most of Sundanese affixes are derivational, so removing the derivational affix as the first step is reasonable. To handle ambiguity, the last recognized affix was returned as the result. As the baseline, a Confix-Stripping Approach which applies Porter Stemmer for the Indonesian language was used. This stemmer shares similarities in terms of affix type, but uses a different stemming order. To observe whether the baseline stems the Sundanese affixed word properly, some features that were not covered by the baseline, such as the infix and allomorph removal, were added. The evaluation was done using 4,453 unique affixed words collected from Sundanese online magazines. The experiment shows that, as a whole, our stemmer outperforms the modified baseline in terms of recognized affixed type accuracy and properly stemmed affixed words. Our stemmer recognized 68.87% of the Sundanese affixes types and produced 96.79% of the correctly affixed words; the modified baseline resulted in 21.70% and 71.59% respectively.

Improving Vector Space Word Representations Via Kernel Canonical Correlation Analysis

Cross-lingual word embeddings are representations for vocabularies of two or more languages in one common continuous vector space and are widely used in various NLP tasks. A simple yet efficient way to generate cross-lingual word embeddings is using canonical correlation analysis (CCA). However, CCA works with the assumption that the vector representations of similar words in different languages are related by a linear relationship. This assumption does not always hold true, especially for substantially different languages. We therefore propose to use kernel canonical correlation analysis (KCCA) to capture non-linear relationships between word embeddings of two languages. By extensively evaluating the resulting word embeddings on three tasks (word similarity, cross-lingual dictionary induction, cross-lingual document classification) across five language pairs, we show that our approach produces essentially better semantic vectors than CCA-based method, especially for substantially different languages.

CLASENTI: A Class-specific Sentiment Analysis Framework

Arabic text sentiment analysis suffers from low accuracy due to Arabic-specific challenges, (e.g., limited resources, morphological complexity, and dialects) and general linguistic issues (e.g., fuzziness, implicit, sarcasm, and spam). The limited resources problem requires efforts to build new and improve Arabic corpora and lexica. We propose a class-specific sentiment analysis (CLASENTI) framework. The framework includes a new annotation approach to build multi-faceted Arabic corpus and lexicon, which are simultaneously annotated with domains, dialects, linguistic issues and polarity strengths. The new corpus and lexicon annotation facilitate the development of new classification model and polarity strength calculation. For the new sentiment classification model, we propose a hybrid model combining corpus-based and lexicon-based models. The corpus-based model has two interrelated phases to build; 1) full-corpus classification models for all facets; and 2) class-specific models trained on filtered subsets of the corpus according to the performances of the full-corpus models. To calculate polarity strengths, the lexicon-based model filters the annotated lexicon based on the specific classes of the domain and dialect. As a case study, we have collected and annotated 15,274 reviews from various sources, including surveys, Facebook comments, and Twitter posts, pertaining to governmental services in an Arab country. CLASENTI framework reaches up to 95% accuracy and 93% F1-Score surpassing the best-known sentiment classifiers that achieve 82% accuracy and 81% F1-Score for Arabic when tested on the same dataset.

Using Communities of Words Derived from Multilingual Word Vectors for Cross-Language Informational Retrieval in Indian Languages

We investigate the use of word embeddings for query translation to improve precision in Cross Language Information Retrieval (CLIR). Word vectors represent words in a distributional space such that syntactically or semantically similar words are close to each other in this space. Multilingual word embeddings are constructed in such a way that similar words across languages have similar vector representations. We explore the effective use of bilingual and multilingual word embeddings learned from comparable corpora of Indic languages to the task of CLIR. We propose a clustering method based on the multilingual word vectors to group similar words across languages. For this we construct a graph with words from multiple languages as nodes and with edges connecting words with similar vectors. We use the Louvain Method for community detection to find communities in this graph. We show that choosing target language words as query translations from the clusters or communities containing the query terms helps in improving CLIR. We also find that better quality query translations are obtained when words from more languages are used to do the clustering even when the additional languages are neither the source of the target language. This is probably because having more similar words across multiple languages help define well-defined dense sub-clusters that help us obtain precise query translations. In this paper, we demonstrate the use of multilingual word embedding and word clusters for CLIR involving Indic languages. We also make available a tool for obtaining related words and the visualizations of the multilingual word vectors for English, Hindi, Bengali, Marathi, Gujarati and Tamil.

Domain-specific Named Entity Recognition with Document-level Optimization

Previous studies normally formulate named entity recognition (NER) as a sequence labeling task and optimize the solution in sentence level. In this paper, we address NER as a document-level optimization problem. First, we apply a state-of-the-art approach, i.e., long short term memory (LSTM), to perform word classification; Second, we define a global objective function with the obtained word classification results and achieve global optimization via Integer Linear Programming (ILP). Specifically, in the ILP-based approach, we propose four kinds of constrains, i.e., label transition, entity length, label consistency, and domain-specific regulation constrains, to incorporate various entity recognition knowledge in document level. Empirical studies demonstrate the effectiveness of the proposed approach to document-level NER.

Graph-based Bilingual Word Embedding for Statistical Machine Translation

Bilingual word embedding has been shown to be helpful for Statistical Machine Translation (SMT). However, most existing methods suffer from two obvious drawbacks. First, they only focus on simple contexts such as an entire document or a fixed sized sliding window to build word embedding and ignore latent useful information from the selected context. Second, the word sense but not the word should be the minimal semantic unit; however, most existing methods are still use word representation. To overcome these drawbacks, this paper presents a novel Graph-based Bilingual Word Embedding (GBWE) method that projects bilingual word senses into a multi-dimensional semantic space. First, a bilingual word co-occurrence graph is constructed using the co-occurrence and pointwise mutual information between the words. Then, maximum complete sub-graphs (cliques), which play the role of a minimal unit for bilingual sense representation, are dynamically extracted according to the contextual information. Consequently, correspondence analysis, principle component analyses and neural networks are used to summarize the clique-word matrix into lower dimensions to build the embedding model. Without contextual information, the proposed GBWE can be applied to lexical translation. In addition, given the contextual information, GBWE is able to give a dynamic solution for bilingual word representations, which can be applied to phrase translation and generation. Empirical results show that GBWE can enhance the performance of lexical translation and Chinese/French-to-English phrase-based SMT.

Words Are Important: Improving Sentiment Analysis in Persian Language by Lexicon Refining

Lexicon-based sentiment analysis aims to address the problem of extracting people[ opinions from their comments on the Web using a pre-defined lexicon of opinionated words. In contrast to machine learning approach, lexicon-based methods are domain-independent methods which do not need a large annotated training corpus and hence are faster. This makes the lexicon-based approach to be prevalent in the sentiment analysis community. However, the story is different for Persian language. In contrast to English, using lexicon-based method in Persian is a new discipline. There are rather limited resources available for sentiment analysis in Persian making the accuracy of the existing lexicon-based methods lower than other languages. In the current study, first an exhaustive investigation of lexicon-based method is performed. Then, two new resources are introduced in order to addresses the problem of resource scarcity for sentiment analysis in Persian; a carefully labeled lexicon of sentiment words, PerLex, and a new hand-made dataset of about 16000 rated documents, PerView. Moreover, a new hybrid method using both machine learning and lexicon-based approach is presented in which PerLex words are used to train the machine learning algorithm. Experiments are carried out on our new PerView dataset. Results indicate that the accuracy of PerLex is higher than the existing NRC and SentiStrength lexicons. Also, the results show that using just adjectives leads to a higher performance in comparison to using NRC or SentiStrength Lexicons. Moreover, the results demonstrate the excellence of using opinionated lexicon terms followed by bigrams as the features employed in machine learning method.

Optimizing Automatic Evaluation of Machine Translation with the ListMLE Approach

Automatic evaluation of machine translation is critical in the evaluation and development of machine translation systems. In this article, we propose a new model for automatic evaluation of machine translation. The proposed model combines standard n-gram precision features and sentence semantic mapping features with neural features, including neural language model probabilities and the embedding distances between translation outputs and their reference translations. We optimize the model with a representative list-wise learning to rank approach, ListMLE, in terms of human ranking assessments. The experimental results on WMT15 Metrics task indicate that the proposed approach has a significantly better correlation with human assessments than several state-of-the-art baseline approaches. In particular, the results confirm that the proposed list-wise learning to rank approach is useful and powerful for optimizing automatic evaluation metrics in terms of human ranking assessments. Deep analysis further reveals that optimizing automatic metrics with the ListMLE approach is reasonable and the neural features can gain considerable improvement over the traditional features.

Comparison of Methods to Annotate Named Entity Corpora

The authors compared two methods for annotating a corpus for the named entity (NE) recognition task using non-expert annotators: i) revising the results of an existing NE recognizer and ii) manually annotating the NEs completely. The annotation time, degree of agreement, and performance were evaluated based on the gold standard. Because there were two annotators for one text for each method, two performances were evaluated: the average performance of both annotators and the performance when at least one annotator is correct. The experiments reveal that semi-automatic annotation is faster, achieves better agreement, and performs better on average. However, they also indicate that sometimes, fully manual annotation should be used for some texts whose document types are substantially different from the training data document types. In addition, the machine learning experiments using semi- automatic and fully manually annotated corpora as training data indicate that the F-measures could be better for some texts when manual instead of semi-automatic annotation was used. Finally, experiments using the annotated corpora for training as additional corpora show that i) the NE recognition performance does not always correspond to the performance of the NE tag annotation and ii) the system trained with the manually annotated corpus outperforms the system trained with the semi-automatically annotated corpus with respect to newswires, even though the existing NE recognizer was mainly trained with newswires.

Weakly Supervised POS Tagging without Disambiguation

Weakly supervised part-of-speech (POS) tagging is to learn to predict the POS tag for a given word in context by making use of partial annotated data instead of the fully tagged corpora. Weakly supervised POS tagging would benefit various natural language processing applications in such languages where tagged corpora are mostly unavailable. In this paper, we propose a novel framework for weakly supervised POS tagging based on a dictionary of words with their possible POS tags. In the constrained error-correcting output codes (ECOC) based approach, a unique L-bit vector is assigned to each POS tag. The set of bitvectors is referred as coding matrix and denoted as M with value {1, -1}. Each column of the coding matrix M specifies a dichotomy over the tag space to learn a binary classifier. For each binary classifier, its training data is generated in the following way: each pair of word and its possible POS tags will be considered as a positive training example only if the whole set of its possible tags falls into the positive dichotomy specified by the column coding; and similarly for negative training examples. Given a word in context, its POS tag is predicted by concatenating the predictive outputs of the L binary classifiers and choosing the tag with the closest distance according to some measure. By incorporating the ECOC strategy, the set of all possible tags for each word is treated as an entirety without the need of performing disambiguation. Moreover, instead of manual feature engineering employed in most previous POS tagging approaches, features for training and testing in the proposed framework are automatically generated using neural language modeling. The proposed framework has been evaluated on three corpora for English, Italian and Malagasy POS tagging, achieving accuracies of 93.21%, 90.9% and 84.5% individually, which shows a significant improvement compared to the state-of-the-art approaches.


Publication Years 2002-2018
Publication Count 337
Citation Count 1149
Available for Download 337
Downloads (6 weeks) 1334
Downloads (12 Months) 12895
Downloads (cumulative) 135538
Average downloads per article 402
Average citations per article 3
First Name Last Name Award
Baoli Li ACM Senior Member (2012)
Bing Liu ACM Fellows (2015)
Robert Luk ACM Senior Member (2007)
Tetsuya Sakai ACM Senior Member (2016)
Limsoon Wong ACM Fellows (2013)
Bulent Yener ACM Senior Member (2013)
Dong Zhou ACM Senior Member (2012)

First Name Last Name Paper Counts
Chengqing Zong 9
Chunghsien Wu 9
Guodong Zhou 7
Masao Utiyama 6
Eiichiro Sumita 6
Garygeunbae Lee 5
Sadao Kurohashi 5
Jianfeng Gao 5
Hitoshi Isahara 5
Kevin Duh 4
Yūji Matsumoto 4
Noriko Kando 4
Hsinmin Wang 4
Naoaki Okazaki 4
Isao Goto 4
Juifeng Yeh 4
Kentaro Inui 4
Andy Way 4
Berlin Chen 4
Swapan Parui 3
Phuoc Tran 3
Qun Liu 3
Byeongchang Kim 3
Susumu Horiguchi 3
Jianyun Nie 3
Jiajun Zhang 3
Pushpak Bhattacharyya 3
Akira Shimazu 3
Long Nguyen 3
Andrew Finch 3
Utpal Sharma 3
Jugal Kalita 3
Tetsuya Sakai 3
Dien Dinh 3
Kuilam Kwok 3
Prasenjit Majumder 3
Teruko Mitamura 3
Jonghoon Lee 3
Kamfai Wong 3
Wenjie Li 3
Umapada Pal 3
Masaki Murata 3
Jiaul Paik 2
Bonnie Dorr 2
Douglas Oard 2
Tong Xiao 2
Muhua Zhu 2
Xuanhieu Phan 2
Grace Ngai 2
Mandar Mitra 2
Neeta Nain 2
Ramy Baly 2
Farid Meziane 2
Shaonan Wang 2
Jong Park 2
Robert Luk 2
Chungchi Huang 2
Bing Liu 2
Jingbo Zhu 2
Kiyotaka Uchimoto 2
Suresh Sundaram 2
Angarai Ramakrishnan 2
Kuanyu Chen 2
Hajime Tsukada 2
Chewlim Tan 2
Kalina Bontcheva 2
Yoshimi Suzuki 2
Shihhung Wu 2
Haitong Yang 2
Qiaoming Zhu 2
Hai Zhao 2
Yusuke Miyao 2
Navanath Saharia 2
David Doermann 2
Degen Huang 2
Katsuhito Sudoh 2
Chengwei Shih 2
David Zajic 2
Leefeng Chien 2
Daisuke Kawahara 2
Hideki Isozaki 2
Alon Lavie 2
Baoli Li 2
Ming Zhou 2
Kehyih Su 2
Chaolin Liu 2
Jiajun Chen 2
Takuya Matsuzaki 2
Ryu Iida 2
Min Zhang 2
Aiti Aw 2
Helen Meng 2
Dipasree Pal 2
Xiaolong Wang 2
Jacques Savoy 2
Hanping Shen 2
Khaled Shaban 2
Wassim El-Hajj 2
Jawad Sadek 2
Hsinhsi Chen 2
Pakchung Ching 2
HungYu Su 2
Chienhsing Chen 2
Ralph Weischedel 2
Sanjeev Khudanpur 2
Tatsunori Mori 2
Jason Chang 2
Imed Zitouni 2
Tiejun Zhao 2
Hazem Hajj 2
Utpal Garain 2
Hideki Mima 2
Atsushi Fujita 2
Chenhui Chu 2
Wenlian Hsu 2
Chungchian Hsu 2
Chinyew Lin 2
Pingche Yang 2
Jun’ichi Tsujii 2
Fumiyo Fukumoto 2
Pascale Fung 2
Dawei Song 2
Hailong Cao 2
Peyman Passban 2
Kehjiann Chen 2
Chenchen Ding 2
Debasis Ganguly 2
Eiichiro Sumita 2
Sophia Ananiadou 2
Anton Leuski 2
Qing Ma 2
Garygeunbae Lee 2
Timothy Baldwin 2
Stephan Vogel 2
Margaret Connell 2
Tan Lee 2
Ali Farghaly 2
Inderjeet Mani 2
Junhui Li 2
Mu Li 2
Toru Ishida 2
Xiaodong Liu 2
Mikio Yamamoto 2
Nizar Habash 2
Baoliang Lu 2
Wenhsiang Lu 2
Toshiaki Nakazawa 2
Jonghyeok Lee 2
Chengwei Lee 2
Benjamin Marie 1
Pengcheng Zhang 1
Emad Mohamed 1
Sangkeun Jung 1
Changki Lee 1
Toru Hitaka 1
Hirofumi Yamamoto 1
Hideki Isozaki 1
Jinsik Lee 1
Welly Naptali 1
JiannCherng Shieh 1
Daming Shi 1
Byoungkee Yi 1
Rohini Srihari 1
Erik Peterson 1
Yair Wiseman 1
Liang Zhou 1
Jonathan May 1
Valentin Tablan 1
Diana Maynard 1
Fuliang Weng 1
Minhwa Chung 1
Michael Paul 1
Peng Wang 1
Masaharu Yoshioka 1
Masanori Nozawa 1
Akinori Fujino 1
T Geetha 1
Afifah Waseem 1
Nitin Madnani 1
Jaime Carbonell 1
Jinxi Xu 1
Kousaku Arita 1
Yan Qu 1
Toshihiko Manabe 1
YuSheng Lai 1
Satoko Marumoto 1
YuChung Lin 1
Yao Qian 1
Chienchung Huang 1
Muhammad Abdul-Mageed 1
Sherri Condon 1
John Aberdeen 1
Farah Zitoune 1
Victoria Rubin 1
David Chiang 1
Jesús Giménez 1
Seiichi Yamamoto 1
Tomoko Izumi 1
Seokbae Jang 1
Yu Shiwen 1
Sunghyon Myaeng 1
Joan Sánchez 1
Ljiljana Dolamic 1
Xipeng Qiu 1
Xuanjing Huang 1
Richardtzonghan Tsai 1
Jing Bai 1
Tubao Ho 1
Joyce Chai 1
Julian Zell 1
Heba El-Fiqi 1
Katsutoshi Hirayama 1
İsmail Altıngövde 1
Junya Norimatsu 1
Erdem Sarigil 1
Fei Cheng 1
Yulun Hsieh 1
Chiahui Chang 1
Mingwen Wang 1
Arjun Das 1
Sumire Uematsu 1
Riyaz Bhat 1
Irshad Bhat 1
Henda Ghézala 1
Mark Hepple 1
Ignatius Ezeani 1
Yansong Feng 1
Pierre Isabelle 1
Shibaprasad Sen 1
Pawan Singh 1
Shengbin Jia 1
Shijia E 1
Danushka Bollegala 1
Lidan Zhang 1
Masatoshi Tsuchiya 1
Robert Damper 1
Yulan He 1
Katsumori Matsushima 1
Avijit Satoskar 1
Yong Chen 1
ChunKai Chen 1
TienTeng Shih 1
Richard Schwartz 1
Prem Natarajan 1
Zhiang Wu 1
Nabin Sharma 1
Jason Chang 1
Baoxun Wang 1
Deyuan Zhang 1
Jinhua Du 1
Yoshiaki Asada 1
Yang Lingpeng 1
Sanae Fujita 1
Sujay Jayakar 1
Fei Xia 1
Alex Waibel 1
Necip Ayan 1
Victor Lavrenko 1
Yihsuan Chuang 1
Chiaying Lee 1
Chunjen Lee 1
M Awad 1
Hamdan Rahman 1
Manoj Sharma 1
Iskandar Keskes 1
Xiaodong He 1
Khaled Shaalan 1
K Shaalan 1
Kenji Imamura 1
Jerry Hobbs 1
Feng Pan 1
Linshan Lee 1
Baotu Ho 1
Deboshree Modak 1
Minh Nguyen 1
Katsuma Narisawa 1
Seokhwan Kim 1
Akihiro Tamura 1
Peishan Tsai 1
Sukhdeep Singh 1
Seunghoon Na 1
Jinjing Xia 1
Suman Mitra 1
Abdelmajid Hamadou 1
Malinda Punchimudiyanse 1
Fang Kong 1
Shanta Phani 1
Eziz Tursun 1
Xinyu Dai 1
Fan Xu 1
Yuzhu Wang 1
Junsheng Zhou 1
Chuan Cheng 1
Uchechukwu Chinedu 1
Yuan Ye 1
Arbi Nasution 1
Daya Lobiyal 1
Khalid Almeman 1
Hongseok Kwon 1
Mehrnoush Shamsfard 1
Oumayma Al Dakkak 1
Kaiyu Huang 1
Shosaku Tanaka 1
Yoichi Tomiura 1
Janming Ho 1
Liming Tseng 1
Minyuh Day 1
TianJian Jiang 1
Kun Wang 1
Hwidong Na 1
Seyed Tahaghoghi 1
Dinh Dien 1
Tran Tri 1
Jungjae Kim 1
Youngsook Hwang 1
Haechang Rim 1
Om Damani 1
JinSeok Lee 1
Ario Ohsato 1
Izumi Suzuki 1
Michael Nossal 1
Dina Demner-Fushman 1
Philip Resnik 1
Hsijian Lee 1
PoChui Luk 1
Wajdi Zaghouani 1
Meihua Chen 1
Lishuang Li 1
Fumito Masui 1
Ngo Bach 1
Sukalpa Chanda 1
Oriol Terrades 1
Yingkuei Yang 1
Qing Li 1
Leah Larkey 1
Mike Maxwell 1
Rebecca Hwa 1
Yuichi Ogawa 1
Yujia Li 1
Mingjun Chen 1
Honglan Jin 1
Yuanxiang Li 1
Christian Hettick 1
Helen Ashman 1
Yaoyong Li 1
Mohd Murah 1
Shahin Salavati 1
Sriram Venkatapathy 1
Shihting Huang 1
Le Sun 1
Cristina España-Bonet 1
Hermann Moisl 1
Tianshun Yao 1
Woosung Kim 1
Diego Linares 1
Ayan Bandyopadhyay 1
Gareth Jones 1
Ling Cao 1
Hideki Shima 1
Hisami Suzuki 1
Kenneth Church 1
Muhua Zhu 1
Shujie Liu 1
Jordi Centelles 1
Utpal Roy 1
Nimit Dhulekar 1
Arjun V 1
Junlin Zhou 1
Kumiko Tanaka-Ishii 1
Hao Zhou 1
Huadong Chen 1
Yanyan Jia 1
Amita Jain 1
Shoushan Li 1
Richard Tsai 1
Heyan Huang 1
Hyunsun Hwang 1
Katsumi Tanaka 1
Takashi Inui 1
Yufeng Chen 1
Sungjin Lee 1
KwopPing Chan 1
Changning Huang 1
Ting Liu 1
Jengwei Lin 1
Yueshi Lee 1
Sriganesh Madhvanath 1
Bobby Nazief 1
Goran Nenadic 1
A Kumaran 1
Huanfeng Ma 1
Satoshi Sekine 1
Jun Luo 1
Hamish Cunningham 1
Kui Xu 1
Yuexian Hou 1
Jeesoo Bang 1
Haiyang Hu 1
Taro Watanabe 1
Liyun Ru 1
Yutaka Matsuo 1
Tsuneaki Kato 1
Niu Zhengyu 1
Tianyong Hao 1
Chunshen Zhu 1
MikeTianjian Jiang 1
Tsunghsien Lee 1
Thu Nguyen 1
Xu Sun 1
Houfeng Wang 1
Albert Brouillette 1
Yueting Zhuang 1
Saras Saraswathi 1
Christopher Cieri 1
Richard Cohen 1
Sriparna Saha 1
Tadaaki Oshio 1
Sumio Fujita 1
Setsuko Nara 1
David Evans 1
Hiroshi Matsuda 1
Gregory Grefenstette 1
Norbert Dinstl 1
Kaifu Lee 1
Joshua Goodman 1
Marine Carpuat 1
Weibin Liang 1
Mark Truran 1
Suliana Sulaiman 1
Nazlia Omar 1
Lamia Belguith 1
Srinivas Bangalore 1
Xiao Liu 1
Robert Moore 1
Longhua Qian 1
Jean Gauvain 1
Xianchao Wu 1
Taichi Asami 1
Yongsheng Yang 1
Minh Le Nguyen 1
Sukomal Pal 1
Johannes Leveling 1
Koichi Takeda 1
Hiroshi Kanayama 1
Guihong Cao 1
Qin Lu 1
Atsuhiro Takasu 1
Keysun Choi 1
Weizheng Yuan 1
Robert Dale 1
Wei Lu 1
Anuj Sharma 1
Sherief Abdallah 1
Yuming Hsieh 1
Lambert Schomaker 1
Abdullah Talib 1
Özgür Ulusoy 1
Hsinhsi Chen 1
Wafa Wali 1
Gilbert Badaro 1
Shibamouli Lahiri 1
Ashish Kankaria 1
Yayun Huang 1
Turghun Osman 1
Ghalip Abdukerim 1
Hanxi Li 1
Deng Cai 1
Keisuke Sakanushi 1
Ramisettyrajeshwara Rao 1
Dipti Sharma 1
Yang Xin 1
Shujian Huang 1
Ikechukwu Onyenwe 1
Yohei Murakami 1
Xiyao Cheng 1
Hyun Kim 1
Himangshu Sarma 1
Shahram Salami 1
Ram Sarkar 1
Kaushik Roy 1
Ercan Solak 1
Olcay Yıldız 1
Lina Sherkawi 1
Qiang Ma 1
Takao Doi 1
Junejei Kuo 1
Mitsuru Ishizuka 1
Josef Van Genabith 1
A Bharath 1
Limsoon Wong 1
ChiaHung Lin 1
Franz Och 1
Ulrich Germann 1
Eduard Hovy 1
Daqing He 1
Yabin Zheng 1
Lixing Xie 1
Mitsuru Ishizuka 1
Makoto Haraguchi 1
Tang Li 1
Yujie Zhang 1
Leigh Gathings 1
Michael Tepper 1
Sanae Fujita 1
Feifan Liu 1
Sarmad Hussain 1
Stephanie Strassel 1
Lori Levin 1
Erik Peterson 1
Ying Zhang 1
Toshiya Ueda 1
Aesun Yoon 1
Hyukchul Kwon 1
Zejing Chuang 1
Rajib Das 1
Faramarz Hendessi 1
Dan Parvaz 1
Christine Doran 1
Charles Blake 1
HoChing Yen 1
Radu Florian 1
Masaaki Nagata 1
Manabu Okumura 1
Jennifer Baldwin 1
James Pustejovsky 1
José Benedí 1
Donna Harman 1
Sucharita Sanyal 1
Tomohide Shibata 1
Atsushi Matsumura 1
Jonghoon Oh 1
TzeLeung Chung 1
Minwoo Jeong 1
Ali Salhi 1
Karthik Krishnamurthi 1
Xiuming Qiao 1
Hussein Abbass 1
Liangliang Liu 1
Indu Chhabra 1
Maad Shatnawi 1
Tongtao Zhang 1
Toru Tanaka 1
Mukesh Goswami 1
Ye Thu 1
Ahmad Al Sallab 1
Ganesh Ramakrishnan 1
Shujian Huang 1
Yu Zhou 1
Rui Wang 1
Chutamanee Onsuwan 1
Hiroki Hanaoka 1
Goutham Tholpadi 1
Yue Zhang 1
Natthawut Kertkeidkachorn 1
Atiwong Suchato 1
Xiaohan She 1
Yang Xiang 1
Jizhou Huang 1
Shiqiang Ding 1
Haifeng Wang 1
Ting Liu 1
Minwoo Jeong 1
Seiichi Nakagawa 1
Yuqing Guo 1
Feipei Lai 1
YiHsun Lee 1
Steve Gunn 1
Daniel Andrade 1
Jelita Asian 1
Mirna Adriani 1
Hugh Williams 1
Nigel Collier 1
Cheongjae Lee 1
Eunju Kim 1
Kyungmi Park 1
Irit Gefner 1
Yuhsien Chiu 1
Yoshihide Chubachi 1
Kareem Darwish 1
Jianqiang Wang 1
Lemao Liu 1
Conghui Zhu 1
Philips Prasetyo 1
Zhiyuan Liu 1
WenLian Hsu 1
Nguyenle Minh 1
Tran Oanh 1
Wenliang Chen 1
Quangthuy Ha 1
Miguel Lezcano 1
Sunam Kim 1
Haizhou Li 1
Jinghui Xiao 1
Asif Ekbal 1
Phil Vines 1
Motoko Ishikawa 1
Yuki Funakoshi 1
David Hull 1
Sora Choi 1
Jungyun Seo 1
Miyoung Kang 1
Y Wong 1
KamFai Wong 1
Jyhshing Jang 1
T Gulliver 1
Seth Kulick 1
Dong Zhou 1
Tim Brailsford 1
Anwitaman Datta 1
Boxing Chen 1
Yanjun Ma 1
Nianwen Xue 1
Lluís Màrquez 1
Yassine Benajiba 1
Takaaki Fukunishi 1
Genichiro Kikui 1
Hiroya Takamura 1
Frank Schilder 1
Lu Qin 1
Pyung Kim 1
Le Zhang 1
Carol Peters 1
Keita Nabeshima 1
Yasushi Inoguchi 1
Rong Jin 1
Eleni Petraki 1
Subhash Panwar 1
Xiaoqing Li 1
Shuling Huang 1
Gina Levow 1
Heng Ji 1
Bülent Yener 1
Liming Zhao 1
Maochuan Su 1
Bilel Gargouri 1
Hsuchun Yen 1
Peifeng Li 1
Yinggong Zhao 1
Taisuke Harada 1
Bilel Elayeb 1
Chiranjib Bhattacharyya 1
Shirish Shevade 1
Chongde Shi 1
Dongyan Zhao 1
Proadpran Punyabukkana 1
Tingxuan Wang 1
Bixiao Cheng 1
Tan Le 1
Muhammad Malik 1
Nilanjana Bhattacharya 1
Partha Roy 1
Razieh Ehsani 1
Cong Zhang 1
Jianjun Ma 1
Garygeunbae Lee 1
Sheng Li 1
YuRen Chen 1
Waikit Lo 1
Jun’ichi Tsujii 1
Hongling Wang 1
Yu Song 1
Jeongwon Cha 1
Seonho Kim 1
Mitesh Khapra 1
Manoj Chinnakotla 1
Kwokping Chan 1
Ada Brunstein 1
Wencheng Lin 1
Dickson Chiu 1
RuYng Chang 1
Ramachandran Jayadevan 1
Eiichrio Sumita 1
Jun'ichi Fukumoto 1
Lauren Hinkle 1
Francis Bond 1
Takaaki Tanaka 1
Fei Huang 1
Nasreen Abduljaleel 1
Katharina Probst 1
James Allan 1
Justin Zobel 1
Tadataka Matsubayashi 1
Makoto Iwayama 1
Daisuke Noda 1
Tamotsu Shirado 1
Jyh Jang 1
Shuilung Chuang 1
A Ghayoori 1
Xiaoqing Ding 1
Andrew Freeman 1
C Rytting 1
Paul Rodrigues 1
Tim Buckwalter 1
Khairuddin Omar 1
Debasis Samanta 1
Kyumars Esmaili 1
Takashi Tsunakawa 1
Patrick Nguyen 1
Lori Lamel 1
Abdelkhalek Messaoudi 1
Satoshi Sato 1
Tomoya Iwakura 1
Beth Sundheim 1
Benfeng Chen 1
Zhao Liu 1
Eric Nichols 1
Le Nguyen 1
Yi Liu 1
Patrick Ye 1
Vijayapal Panuganti 1
Vishnu Bulusu 1
Cungen Cao 1
Marta Costa-Jussà 1
Mairidan Wushouer 1
Donghui Lin 1
Deepti Khanduja 1
Tapan Bhowmik 1
Aritra Chowdhury 1
Kevin Knight 1
Prakash Choudhary 1
Makoto Yasuhara 1
Oguz Yilmaz 1
Wenyi Chen 1
Ravinda Meegama 1
Maoxi Li 1
Kanwen Tien 1
Thanaruk Theeramunkong 1
Ibrahim Bounhas 1
Diab Abuaiadah 1
Hirona Touji 1
Zhongye Jia 1
Xinyu Dai 1
Anja Chaibi 1
Chao Lv 1
Sreelekha S 1
Ankan Bhattacharyya 1
Ping Jian 1
Nada Ghneim 1
Jiahuan Pei 1
Maozhen Li 1
Nguyentuan Duc 1
Haifeng Wang 1
Wanxiang Che 1
Chenglung Sung 1
Chiawei Wu 1
Jonghyeok Lee 1
Pham Thao 1
Kyoungduk Kim 1
Smruthi Mukund 1
Yoshiki Mikami 1
Ralph Grishman 1
Michael Subotin 1
Wei Li 1
Andrew McCallum 1
Chiching Lin 1
Yi Zhuang 1
Qing Li 1
Chengjie Sun 1
Maosong Sun 1
Yang Zhang 1
Lian Zhao 1
Ji Donghong 1
Cam Nguyen 1
David Martínez 1
Yang Liu 1
Jinshea Kuo 1
Yi Zhuang 1
Lei Chen 1
Sana Gul 1
Ariadna Llitjos 1
Rachel Reynolds 1
Minhua Lai 1
Hisao Mase 1
Makoto Koyama 1
Harksoo Kim 1
Wai Lau 1
Jun'ichi Tsujii 1
Mingjing Li 1
Jiangchun Chen 1
Sarah Wayland 1
Ryuichiro Higashinaka 1
Shihhsiang Lin 1
Haizhou Li 1
Philipp Koehn 1
Mei Yang 1
Peng Zhang 1
Qun Liu 1
Kuniko Saito 1
Benjamin Han 1
Jingbo Zhu 1
Samaresh Maiti 1
Minh Pham 1
Yotaro Watanabe 1
Junta Mizuno 1
Jun Adachi 1
Diklun Lee 1
Adnan Yahya 1
Jannik Strötgen 1
Ayser Armiti 1
Tran Van Canh 1
Michael Gertz 1
Yuji Matsumoto 1
Arafat Awajan 1
Minghong Bai 1
Lunghao Lee 1
Dil Hakro 1
Rifat Ozcan 1
Arindam Biswas 1
Shihhung Liu 1
Wenlian Hsu 1
Chienlung Chou 1
Yating Yang 1
Abhisek Chakrabarty 1
Nitin Ramrakhiyani 1
Nongnuch Ketui 1
B Kumari 1
Hai Zhao 1
Haoran Li 1
Marwa Naili 1
Ying Chen 1
Hunyoung Jung 1
Seunghoon Na 1

Affiliation Paper Counts
Ryukoku University 1
Nagoya University 1
Waikato Institute of Technology 1
Universiti Sains Malaysia 1
University of Michigan 1
Chonbuk National University 1
University of Kurdistan 1
Cairo University Faculty of Engineering 1
University of Victoria 1
Middle East Technical University 1
Pondicherry Engineering College 1
Newcastle University, United Kingdom 1
Bose Institute 1
Cornell University 1
Fujitsu Ltd. 1
United Arab Emirates University 1
National Research Council Canada 1
University of Colorado at Colorado Springs 1
Japan Patent Information Organization 1
The University of Western Ontario 1
National Chiao Tung University Taiwan 1
Zhejiang Gongshang University 1
University of Texas at Austin 1
Yuan Ze University 1
Catholic University of Daegu 1
Hangzhou Dianzi University 1
Seoul National University 1
AT&T Inc. 1
Dharmsinh Desai University 1
Japan Society for the Promotion of Science 1
Robert Bosch GmbH 1
The Institute of Behavioral Sciences 1
Sogang University 1
Mie University 1
Tianjin University 1
Macquarie University 1
Kobe University Faculty of Maritime Sciences 1
Nanjing Normal University 1
Brunel University London 1
Information and Communications University 1
Tunghai University 1
Anna University 1
Nnamdi Azikiwe University 1
Jawaharlal Nehru Technological University, Hyderabad 1
University of Canberra 1
Chungnam National University 1
Industrial Technology Research Institute of Taiwan 1
National Institute of Standards and Technology 1
Shanghai University of International Business and Economics 1
National Institute of Advanced Industrial Science and Technology 1
Al Qassim University 1
University of Teesside 1
University Michigan Ann Arbor 1
University of Edinburgh 1
University of Quebec in Montreal 1
University of Hamburg 1
Ming Chuan University 1
Columbia University 1
Jawaharlal Nehru University 1
Institute of Computing Technology Chinese Academy of Sciences 1
Indian Institute of Technology Roorkee 1
Ritsumeikan University 1
Space and Naval Warfare Systems Center San Diego 1
Universidad Javeriana 1
University of Sindh 1
University of the Punjab Lahore 1
Princess Sumaya University 1
Open University of Sri Lanka 1
Damascus University 1
Istituto di Scienza e Tecnologie dell'Informazione A. Faedo 1
Baosteel Co., Ltd. 1
University of Sri Jayewardenepura 1
Gokaraju Rangaraju Institute of Engineering & Technology 1
Janya, Inc. 1
Universiti Pendidikan Sultan Idris 1
New York University Abu Dhabi 1
Institute of Scientific and Technical Information of China 1
Ritsumeikan University, Biwako-Kusatsu 1
Turgut Ozal University 1
Jawaharlal Nehru Technological University, Kakinada 1
Emirates College of Technology 1
Christ University, Bangalore 1
National Institute of Technology Manipur 1
SK Telecom Co., Ltd. 1
Kangwon National University 2
Indian Institute of Engineering Science and Technology, Shibpur, Howrah, India 2
Zhejiang University 2
Indian Institute of Technology, Kharagpur 2
City University of New York 2
Hebrew University of Jerusalem 2
University of Texas at Dallas 2
University of Groningen 2
HP Labs 2
Doshisha University 2
Universidad Politecnica de Valencia 2
Robert Gordon University 2
Open University 2
Hokkaido University 2
University of Nottingham 2
University of Pittsburgh 2
Japan Science and Technology Agency 2
Brandeis University 2
Monterey Institute of International Studies 2
Jadavpur University 2
Indiana University 2
New York University 2
University of Calcutta 2
University of Southampton 2
Chaoyang University of Technology 2
Microsoft Corporation 2
National Taiwan University of Science and Technology 2
Isfahan University of Technology 2
University of New South Wales 2
Uiduk University 2
Tokyo Institute of Technology 2
University at Buffalo, State University of New York 2
Shahid Beheshti University 2
University of Indonesia 2
Vietnam National University 2
Birzeit University 2
University of Qatar 2
Higher Institute for Applied Sciences and Technology Syria 2
Huawei Technologies Co., Ltd. 2
Universite de Toulouse 2
Dhirubhai Ambani Institute of Information and Communication Technology 2
Singapore University of Technology and Design 2
IBM, Japan 2
International Institute of Information Technology Hyderabad 3
University of Neuchatel 3
Toyohashi University of Technology 3
University of Manchester 3
Queens College, City University of New York 3
Johns Hopkins University 3
Korea University 3
Nanyang Technological University 3
Pusan National University 3
Isik University 3
Kyushu University 3
Thammasat University 3
China Agricultural University 3
Bilkent University 3
IBM Thomas J. Watson Research Center 3
Nagaoka University of Technology 3
Panjab University 3
Chulalongkorn University 3
Research Organization of Information and Systems National Institute of Informatics 3
University of Southern California 3
Michigan State University 3
Northeastern University China 3
Laobratoire d'Informatique pour la Mecanique et les Sciences de l'Ingenieur 3
University of Manouba 3
National University of Computer and Emerging Sciences Lahore 3
British University in Dubai 3
Tongji University 3
Ton-Duc-Thang University 3
Indian Institute of Technology 3
University of Colorado at Boulder 4
Advanced Telecommunications Research Institute International (ATR) 4
Universiti Kebangsaan Malaysia 4
Hitachi, Ltd. 4
Tezpur University 4
University of Salford 4
University of Yamanashi 4
Fudan University 4
Jiangxi Normal University 4
City University of Hong Kong 4
University of Washington, Seattle 4
Beijing Institute of Technology 4
National University of Singapore 4
Yokohama National University 4
Toshiba Corporation 4
Georgetown University 4
National Central University Taiwan 4
Korea Advanced Institute of Science & Technology 4
University of Sfax 4
Xinjiang Technical Institute of Physics and Chemistry 4
University of Pennsylvania 5
The University of Hong Kong 5
Universitat Politecnica de Catalunya 5
University of Montreal 5
RMIT University 5
University of Heidelberg 5
National Chiayi University 5
Rensselaer Polytechnic Institute 5
University of Melbourne 5
National Chengchi University 5
Indian Institute of Science, Bangalore 6
National Yunlin University of Science and Technology 6
National Taiwan Normal University 6
Northeastern University 6
Hong Kong University of Science and Technology 7
BBN Technologies 7
MITRE Corporation 7
American University of Beirut 7
JustSystems Corporation 7
Institute for Infocomm Research, A-Star, Singapore 8
University of Massachusetts Amherst 8
Chinese Academy of Sciences 8
Shanghai Jiaotong University 8
University of Sheffield 9
Dalian University of Technology 9
University of Tsukuba 9
Peking University 9
University of Southern California, Information Sciences Institute 9
Microsoft Research 9
Tsinghua University 9
Hong Kong Polytechnic University 11
Indian Institute of Technology, Bombay 11
Nanjing University 11
Microsoft Research Asia 11
National Taiwan University 12
Tohoku University 13
Japan Advanced Institute of Science and Technology 14
Institute of Automation Chinese Academy of Sciences 15
Nara Institute of Science and Technology 15
Soochow University 16
Kyoto University 16
National Tsing Hua University 16
Dublin City University 16
Chinese University of Hong Kong 17
Carnegie Mellon University 17
Harbin Institute of Technology 20
University of Tokyo 20
Nippon Telegraph and Telephone Corporation 20
Indian Statistical Institute, Kolkata 22
National Cheng Kung University 25
University of Maryland 27
Pohang University of Science and Technology 27
Academia Sinica Taiwan 28
Japan National Institute of Information and Communications Technology 40

ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP)

Volume 17 Issue 3, May 2018
Volume 17 Issue 2, February 2018

Volume 17 Issue 1, November 2017
Volume 16 Issue 4, September 2017
Volume 16 Issue 3, April 2017

Volume 16 Issue 2, December 2016 TALLIP Notes and Regular Papers
Volume 16 Issue 1, December 2016 TALLIP Notes and Regular Papers
Volume 15 Issue 4, June 2016
Volume 15 Issue 3, March 2016
Volume 15 Issue 2, February 2016
Volume 15 Issue 1, January 2016

Volume 14 Issue 4, October 2015 Special Issue on Chinese Spell Checking
Volume 14 Issue 3, June 2015
Volume 14 Issue 2, March 2015
Volume 14 Issue 1, January 2015

Volume 13 Issue 4, December 2014
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Volume 13 Issue 2, June 2014
Volume 13 Issue 1, February 2014

Volume 12 Issue 4, October 2013
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Volume 12 Issue 2, June 2013
Volume 12 Issue 1, March 2013

Volume 11 Issue 4, December 2012 Special Issue on RITE
Volume 11 Issue 3, September 2012
Volume 11 Issue 2, June 2012
Volume 11 Issue 1, March 2012

Volume 10 Issue 4, December 2011
Volume 10 Issue 3, September 2011
Volume 10 Issue 2, June 2011
Volume 10 Issue 1, March 2011

Volume 9 Issue 4, December 2010
Volume 9 Issue 3, September 2010
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Volume 9 Issue 1, March 2010

Volume 8 Issue 4, December 2009
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Volume 8 Issue 1, March 2009

Volume 7 Issue 4, November 2008
Volume 7 Issue 3, August 2008
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Volume 6 Issue 4, December 2007
Volume 6 Issue 3, November 2007
Volume 6 Issue 2, September 2007
Volume 6 Issue 1, April 2007

Volume 5 Issue 4, December 2006
Volume 5 Issue 3, September 2006
Volume 5 Issue 2, June 2006
Volume 5 Issue 1, March 2006

Volume 4 Issue 4, December 2005
Volume 4 Issue 3, September 2005
Volume 4 Issue 2, June 2005
Volume 4 Issue 1, March 2005

Volume 3 Issue 4, December 2004
Volume 3 Issue 3, September 2004
Volume 3 Issue 2, June 2004
Volume 3 Issue 1, March 2004 Special Issue on Temporal Information Processing

Volume 2 Issue 4, December 2003
Volume 2 Issue 3, September 2003
Volume 2 Issue 2, June 2003
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Volume 1 Issue 4, December 2002
Volume 1 Issue 3, September 2002
Volume 1 Issue 2, June 2002
Volume 1 Issue 1, March 2002
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