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Workshop on Arabic Natural Language Processing最新文献

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Assessing the Linguistic Knowledge in Arabic Pre-trained Language Models Using Minimal Pairs 使用最小对评估阿拉伯语预训练语言模型中的语言知识
Workshop on Arabic Natural Language Processing Pub Date : 1900-01-01 DOI: 10.18653/v1/2022.wanlp-1.17
Wafa Abdullah Alrajhi, H. Al-Khalifa, Abdulmalik Alsalman
{"title":"Assessing the Linguistic Knowledge in Arabic Pre-trained Language Models Using Minimal Pairs","authors":"Wafa Abdullah Alrajhi, H. Al-Khalifa, Abdulmalik Alsalman","doi":"10.18653/v1/2022.wanlp-1.17","DOIUrl":"https://doi.org/10.18653/v1/2022.wanlp-1.17","url":null,"abstract":"Despite the noticeable progress that we recently witnessed in Arabic pre-trained language models (PLMs), the linguistic knowledge captured by these models remains unclear. In this paper, we conducted a study to evaluate available Arabic PLMs in terms of their linguistic knowledge. BERT-based language models (LMs) are evaluated using Minimum Pairs (MP), where each pair represents a grammatical sentence and its contradictory counterpart. MPs isolate specific linguistic knowledge to test the model’s sensitivity in understanding a specific linguistic phenomenon. We cover nine major Arabic phenomena: Verbal sentences, Nominal sentences, Adjective Modification, and Idafa construction. The experiments compared the results of fifteen Arabic BERT-based PLMs. Overall, among all tested models, CAMeL-CA outperformed the other PLMs by achieving the highest overall accuracy.","PeriodicalId":355149,"journal":{"name":"Workshop on Arabic Natural Language Processing","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115330104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Improving POS Tagging for Arabic Dialects on Out-of-Domain Texts 域外文本中阿拉伯方言词性标注的改进
Workshop on Arabic Natural Language Processing Pub Date : 1900-01-01 DOI: 10.18653/v1/2022.wanlp-1.22
Noor Abo Mokh, D. Dakota, Sandra Kübler
{"title":"Improving POS Tagging for Arabic Dialects on Out-of-Domain Texts","authors":"Noor Abo Mokh, D. Dakota, Sandra Kübler","doi":"10.18653/v1/2022.wanlp-1.22","DOIUrl":"https://doi.org/10.18653/v1/2022.wanlp-1.22","url":null,"abstract":"We investigate part of speech tagging for four Arabic dialects (Gulf, Levantine, Egyptian, and Maghrebi), in an out-of-domain setting. More specifically, we look at the effectiveness of 1) upsampling the target dialect in the training data of a joint model, 2) increasing the consistency of the annotations, and 3) using word embeddings pre-trained on a large corpus of dialectal Arabic. We increase the accuracy on average by about 20 percentage points.","PeriodicalId":355149,"journal":{"name":"Workshop on Arabic Natural Language Processing","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115249631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
AraProp at WANLP 2022 Shared Task: Leveraging Pre-Trained Language Models for Arabic Propaganda Detection AraProp在WANLP 2022共享任务:利用预训练的语言模型进行阿拉伯语宣传检测
Workshop on Arabic Natural Language Processing Pub Date : 1900-01-01 DOI: 10.18653/v1/2022.wanlp-1.56
Gaurav Singh
{"title":"AraProp at WANLP 2022 Shared Task: Leveraging Pre-Trained Language Models for Arabic Propaganda Detection","authors":"Gaurav Singh","doi":"10.18653/v1/2022.wanlp-1.56","DOIUrl":"https://doi.org/10.18653/v1/2022.wanlp-1.56","url":null,"abstract":"This paper presents the approach taken for the shared task on Propaganda Detection in Arabic at the Seventh Arabic Natural Language Processing Workshop (WANLP 2022). We participated in Sub-task 1 where the text of a tweet is provided, and the goal is to identify the different propaganda techniques used in it. This problem belongs to multi-label classification. For our solution, we approached leveraging different transformer based pre-trained language models with fine-tuning to solve this problem. We found that MARBERTv2 outperforms in terms of performance where F1-macro is 0.08175 and F1-micro is 0.61116 compared to other language models that we considered. Our method achieved rank 4 in the testing phase of the challenge.","PeriodicalId":355149,"journal":{"name":"Workshop on Arabic Natural Language Processing","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124729018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Developing a Tag-Set and Extracting the Morphological Lexicons to Build a Morphological Analyzer for Egyptian Arabic 建立埃及阿拉伯语词法分析器的标记集及词法词汇提取
Workshop on Arabic Natural Language Processing Pub Date : 1900-01-01 DOI: 10.18653/v1/2022.wanlp-1.14
Amany Fashwan, S. Alansary
{"title":"Developing a Tag-Set and Extracting the Morphological Lexicons to Build a Morphological Analyzer for Egyptian Arabic","authors":"Amany Fashwan, S. Alansary","doi":"10.18653/v1/2022.wanlp-1.14","DOIUrl":"https://doi.org/10.18653/v1/2022.wanlp-1.14","url":null,"abstract":"This paper sheds light on an in-progress work for building a morphological analyzer for Egyptian Arabic (EGY). To build such a tool, a tag-set schema is developed depending on a corpus of 527,000 EGY words covering different sources and genres. This tag-set schema is used in annotating about 318,940 words, morphologically, according to their contexts. Each annotated word is associated with its suitable prefix(s), original stem, tag, suffix(s), glossary, number, gender, definiteness, and conventional lemma and stem. These morphologically annotated words, in turns, are used in developing the proposed morphological analyzer where the morphological lexicons and the compatibility tables are extracted and tested. The system is compared with one of best EGY morphological analyzers; CALIMA.","PeriodicalId":355149,"journal":{"name":"Workshop on Arabic Natural Language Processing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121691498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
NGU CNLP atWANLP 2022 Shared Task: Propaganda Detection in Arabic NGU CNLP atWANLP 2022共享任务:阿拉伯语宣传检测
Workshop on Arabic Natural Language Processing Pub Date : 1900-01-01 DOI: 10.18653/v1/2022.wanlp-1.66
A. S. Hussein, Abu Bakr Soliman Mohammad, Mohamed Ibrahim, Laila H. Afify, S. El-Beltagy
{"title":"NGU CNLP atWANLP 2022 Shared Task: Propaganda Detection in Arabic","authors":"A. S. Hussein, Abu Bakr Soliman Mohammad, Mohamed Ibrahim, Laila H. Afify, S. El-Beltagy","doi":"10.18653/v1/2022.wanlp-1.66","DOIUrl":"https://doi.org/10.18653/v1/2022.wanlp-1.66","url":null,"abstract":"This paper presents the system developed by the NGU_CNLP team for addressing the shared task on Propaganda Detection in Arabic at WANLP 2022. The team participated in the shared tasks’ two sub-tasks which are: 1) Propaganda technique identification in text and 2) Propaganda technique span identification. In the first sub-task, the goal is to detect all employed propaganda techniques in some given piece of text out of a possible 17 different techniques or to detect that no propaganda technique is being used in that piece of text. As such, this first sub-task is a multi-label classification problem with a pool of 18 possible labels. Subtask 2 extends sub-task 1, by requiring the identification of the exact text span in which a propaganda technique was employed, making it a sequence labeling problem. For task 1, a combination of a data augmentation strategy coupled with an enabled transformer-based model comprised our classification model. This classification model ranked first amongst the 14 systems participating in this subtask. For sub-task two, a transfer learning model was adopted. The system ranked third among the 3 different models that participated in this subtask.","PeriodicalId":355149,"journal":{"name":"Workshop on Arabic Natural Language Processing","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124093245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Domain-Adapted BERT-based Models for Nuanced Arabic Dialect Identification and Tweet Sentiment Analysis 基于领域适应bert的阿拉伯语方言识别和微博情感分析模型
Workshop on Arabic Natural Language Processing Pub Date : 1900-01-01 DOI: 10.18653/v1/2022.wanlp-1.43
Giyaseddin Bayrak, Abdul Majeed Issifu
{"title":"Domain-Adapted BERT-based Models for Nuanced Arabic Dialect Identification and Tweet Sentiment Analysis","authors":"Giyaseddin Bayrak, Abdul Majeed Issifu","doi":"10.18653/v1/2022.wanlp-1.43","DOIUrl":"https://doi.org/10.18653/v1/2022.wanlp-1.43","url":null,"abstract":"This paper summarizes the solution of the Nuanced Arabic Dialect Identification (NADI) 2022 shared task. It consists of two subtasks: a country-level Arabic Dialect Identification (ADID) and an Arabic Sentiment Analysis (ASA). Our work shows the importance of using domain-adapted models and language-specific pre-processing in NLP task solutions. We implement a simple but strong baseline technique to increase the stability of fine-tuning settings to obtain a good generalization of models. Our best model for the Dialect Identification subtask achieves a Macro F-1 score of 25.54% as an average of both Test-A (33.89%) and Test-B (19.19%) F-1 scores. We also obtained a Macro F-1 score of 74.29% of positive and negative sentiments only, in the Sentiment Analysis task.","PeriodicalId":355149,"journal":{"name":"Workshop on Arabic Natural Language Processing","volume":"246 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121481202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Generative Approach for Gender-Rewriting Task with ArabicT5 基于ArabicT5的性别改写任务生成方法
Workshop on Arabic Natural Language Processing Pub Date : 1900-01-01 DOI: 10.18653/v1/2022.wanlp-1.55
Sultan Alrowili, Vijay K. Shanker
{"title":"Generative Approach for Gender-Rewriting Task with ArabicT5","authors":"Sultan Alrowili, Vijay K. Shanker","doi":"10.18653/v1/2022.wanlp-1.55","DOIUrl":"https://doi.org/10.18653/v1/2022.wanlp-1.55","url":null,"abstract":"Addressing the correct gender in generative tasks (e.g., Machine Translation) has been an overlooked issue in the Arabic NLP. However, the recent introduction of the Arabic Parallel Gender Corpus (APGC) dataset has established new baselines for the Arabic Gender Rewriting task. To address the Gender Rewriting task, we first pre-train our new Seq2Seq ArabicT5 model on a 17GB of Arabic Corpora. Then, we continue pre-training our ArabicT5 model on the APGC dataset using a newly proposed method. Our evaluation shows that our ArabicT5 model, when trained on the APGC dataset, achieved competitive results against existing state-of-the-art methods. In addition, our ArabicT5 model shows better results on the APGC dataset compared to other Arabic and multilingual T5 models.","PeriodicalId":355149,"journal":{"name":"Workshop on Arabic Natural Language Processing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128827387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
ArabIE: Joint Entity, Relation and Event Extraction for Arabic 阿拉伯语的联合实体、关系和事件提取
Workshop on Arabic Natural Language Processing Pub Date : 1900-01-01 DOI: 10.18653/v1/2022.wanlp-1.31
Niama El Khbir, Nadi Tomeh, Thierry Charnois
{"title":"ArabIE: Joint Entity, Relation and Event Extraction for Arabic","authors":"Niama El Khbir, Nadi Tomeh, Thierry Charnois","doi":"10.18653/v1/2022.wanlp-1.31","DOIUrl":"https://doi.org/10.18653/v1/2022.wanlp-1.31","url":null,"abstract":"Previous work on Arabic information extraction has mainly focused on named entity recognition and very little work has been done on Arabic relation extraction and event recognition. Moreover, modeling Arabic data for such tasks is not straightforward because of the morphological richness and idiosyncrasies of the Arabic language. We propose in this article the first neural joint information extraction system for the Arabic language.","PeriodicalId":355149,"journal":{"name":"Workshop on Arabic Natural Language Processing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128406632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Coreference Annotation of an Arabic Corpus using a Virtual World Game 使用虚拟世界游戏的阿拉伯语料库的共同参考注释
Workshop on Arabic Natural Language Processing Pub Date : 1900-01-01 DOI: 10.18653/v1/2022.wanlp-1.37
Wateen A. Aliady, Abdulrahman Aloraini, Chris Madge, Juntao Yu, R. Bartle, Massimo Poesio
{"title":"Coreference Annotation of an Arabic Corpus using a Virtual World Game","authors":"Wateen A. Aliady, Abdulrahman Aloraini, Chris Madge, Juntao Yu, R. Bartle, Massimo Poesio","doi":"10.18653/v1/2022.wanlp-1.37","DOIUrl":"https://doi.org/10.18653/v1/2022.wanlp-1.37","url":null,"abstract":"Coreference resolution is a key aspect of text comprehension, but the size of the available coreference corpora for Arabic is limited in comparison to the size of the corpora for other languages. In this paper we present a Game-With-A-Purpose called Stroll with a Scroll created to collect from players coreference annotations for Arabic. The key contribution of this work is the embedding of the annotation task in a virtual world setting, as opposed to the puzzle-type games used in previously proposed Games-With-A-Purpose for coreference.","PeriodicalId":355149,"journal":{"name":"Workshop on Arabic Natural Language Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115518439","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Adversarial Text-to-Speech for low-resource languages 针对低资源语言的对抗性文本到语音
Workshop on Arabic Natural Language Processing Pub Date : 1900-01-01 DOI: 10.18653/v1/2022.wanlp-1.8
Ashraf Elneima, Mikolaj Binkowski
{"title":"Adversarial Text-to-Speech for low-resource languages","authors":"Ashraf Elneima, Mikolaj Binkowski","doi":"10.18653/v1/2022.wanlp-1.8","DOIUrl":"https://doi.org/10.18653/v1/2022.wanlp-1.8","url":null,"abstract":"In this paper we propose a new method for training adversarial text-to-speech (TTS) models for low-resource languages using auxiliary data. Specifically, we modify the MelGAN (Kumar et al., 2019) architecture to achieve better performance in Arabic speech generation, exploring multiple additional datasets and architectural choices, which involved extra discriminators designed to exploit high-frequency similarities between languages. In our evaluation, we used subjective human evaluation, MOS-Mean Opinion Score, and a novel quantitative metric, the Fréchet Wav2Vec Distance, which we found to be well correlated with MOS. Both subjectively and quantitatively, our method outperformed the standard MelGAN model.","PeriodicalId":355149,"journal":{"name":"Workshop on Arabic Natural Language Processing","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125995066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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