Taiwan

In this paper, we describe the development of a communication support system that detects erroneous translations to facilitate cross-lingual communications due to the limitations of current machine chat translation methods.
We trained an error detector as the baseline of the system and constructed a new Japanese–English bilingual chat corpus, BPersona-chat, which comprises multi-turn colloquial chats augmented with crowdsourced quality ratings.
The error detector can serve as an encouraging foundation for more advanced erroneous translation detection systems.

IJCNLP-AACL 2022

Chat Translation Error Detection for Assisting Cross-lingual Communications

dialogue translation

chat translation

evaluation

machine translation

dataset

The International Conference on Computational Processing of Portuguese (PROPOR) is the main event in the area of human language processing that is focused on theoretical and technological issues of written and spoken Portuguese and Galician. The meeting has been a very rich forum for the exchange of ideas and partnerships for the research and industry communities dedicated to the automated processing of Portuguese, promoting the development of methodologies, resources and projects that can be shared among researchers and practitioners in the field.

Find more information and pay the registration fee on [event organizer’s website](https://sites.universidadedefortaleza.com/propor2022/?page_id=401)

PROPOR 2022

The International Conference on Computational Processing of Portuguese (PROPOR) is the main event in the area of human language processing that is focused on theoretical and technological issues of written and spoken Portuguese and Galician.

workshop paper

The AACL, Asia-Pacific Chapter of the Association for Computational Linguistics, and the AFNLP, Asian Federation of Natural Language Processing, invite you to participate in the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL) and the 10th International Joint Conference on Natural Language Processing (IJCNLP). 
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A registration is required to access this event. Access to the event site will be granted to all registered attendees on **November 16th**. If you have not already done so, please register using the link below:
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<br>https://conference.iis.sinica.edu.tw/servlet/Register?ConferenceID=411

Registration Is Required

The AACL, Asia-Pacific Chapter of the Association for Computational Linguistics, and the AFNLP, Asian Federation of Natural Language Processing, invite you to participate in the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL) and the 10th International Joint Conference on Natural Language Processing (IJCNLP). 

Questioning Implicit Assumptions in our Evaluation Methodologies

GLARE: Generative Left-to-right AdversaRial Examples

 MasakhaNER: Named Entity Recognition Dataset for 20 African languages.

SUMEval shared task overview

NTREX-128 -- News Test References for MT Evaluation of 128 Languages

Significant progress has been made on Indonesian NLP. Nevertheless, exploration of the codemixing phenomenon in Indonesian is limited, despite many languages being frequently mixed with Indonesian. In this work, we explore codemixing in Indonesian with four embedded languages, i.e., English, Sundanese, Javanese, and Malay; and introduce IndoRobusta, a framework to evaluate and improve the code-mixing robustness. Our analysis shows that the pretraining corpus bias affects the model’s ability to better handle Indonesian-English codemixing rather than other local languages, despite having higher language diversity.

IndoRobusta: Towards Robustness Against Diverse Code-Mixed Indonesian Local Languages

Amadís de Gaula (AG) and its sequel Sergas de Esplandián (SE) are masterpieces of medieval Spanish chivalric romances. Much debate has been devoted to the role played by their purported author Garci Rodríguez de Montalvo. According to the prologue of AG, which consists of four books, the author allegedly revised the first three books that were in circulation at that time and added the fourth book and SE. However, the extent to which Montalvo edited the materials at hand to compose the extant works has yet to be explored extensively. To address this question, we applied stylometric techniques for the first time. Specifically, we investigated the stylistic differences (if any) between the first three books of AG and his own extensions. Literary style is represented as usage of parts-of-speech n-grams. We performed principal component analysis and k-means to demonstrate that Montalvo's retouching on the first book was minimal, while revising the second and third books in such a way that they came to moderately resemble his authentic creation, that is, the fourth book and SE. Our findings empirically corroborate suppositions formulated from philological viewpoints.

A Stylometric Analysis of Amadís de Gaula and Sergas de Esplandián

This paper is a methodological exploration of the origin of mood in early modern and modern Finnish literary texts using computational methods. We discuss the pre-processing steps as well as the various natural language processing tools used to try to pinpoint where mood can be best detected in text. We also share several tools and resources developed during this process. Our early attempts suggest that overall mood can be computationally detected in the first three paragraphs of a book.

Computational Exploration of the Origin of Mood in Literary Texts

Election speeches play an integral role in communicating the vision and mission of the candidates. From lofty promises to mud-slinging, the electoral candidate accounts for all. However, there remains an open question about what exactly wins over the voters. In this work, we used state-of-the-art natural language processing methods to study the speeches and sentiments of the Republican candidates and Democratic candidates fighting for the 2020 US Presidential election. Comparing the racial dichotomy of the United States, we analyze what led to the victory and defeat of the different candidates. We believe this work will inform the election campaigning strategy and provide a basis for communicating to diverse crowds.

Chat Translation Error Detection for Assisting Cross-lingual Communications

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