Invited Speakers

Nizar Habash

Keynote
Computational Modeling of Gender in Arabic.  

[Slides available here]

Abstract
Arabic is a morphologically rich language with many modern dialects and a large written tradition. We present some of the linguistics particularities of Arabic, focusing on its grammatical gender, contextualized within modern discourses around gender and power and their intersections with approaches to computational modeling. We report on recent advances in the modeling of gender in Arabic and identify open problems and challenges.


Speaker Bio

Nizar Habash is a Professor of Computer Science at New York University Abu Dhabi (NYUAD). He is also the director of the Computational Approaches to Modeling Language (CAMeL) Lab.  Professor Habash specializes in natural language processing and computational linguistics. Before joining NYUAD in 2014, he was a research scientist at Columbia University's Center for Computational Learning Systems. He received his PhD in Computer Science from the University of Maryland College Park in 2003.  He has two bachelor's degrees, one in Computer Engineering and one in Linguistics and Languages. His research includes extensive work on machine translation, morphological analysis, and computational modeling of Arabic and its dialects. Professor Habash has been a principal investigator or co-investigator on over 25 research grants. And he has over 200 publications, including a book entitled "Introduction to Arabic Natural Language Processing". His website is www.nizarhabash.com. 

Danielle Saunders

Keynote
Gender-inclusive machine translation: Challenges and needs

[Slides available here]

Abstract
In recent years the research community has proposed a variety of ways to address gender bias in machine translation. This talk will cover some challenges that arise when applying those methods at scale in terms of data size and language variety. The talk will then look at possible requirements of the future, including context and neutrality, and the new challenges they will raise.

Speaker Bio
Danielle Saunders is a research scientist at RWS Language Weaver working on machine translation. She completed her PhD on domain adaptation for machine translation in 2021. Her research focuses on the ways we can understand and control translation systems when translating unusual or ambiguous terms. She has several publications on the effect of gender bias on machine translation and ways to mitigate it.  Her website is https://dcsaunders.github.io/.

Laura Hekanaho & Anna Merikallio

Keynote

Gender in Finnish: Perspectives from linguistics and translation studies 

Abstract

In this joint presentation, we report on two studies investigating gender in Finnish. The Finnish language lacks markers of grammatical and pronominal gender, but still makes use of lexical gender (e.g., in words such as mother, sister). Whilst often mistakenly described as “gender-neutral”, Finnish includes many gendered epicenes (e.g., so-called masculine generics, such as esimies, supervisor[+masc]). In addition, other linguistic items such as adjectives may carry gendered connotations (e.g., kaunis, beautiful vs. komea, handsome). 

Focusing on gender exclusive and inclusive language, Laura Hekanaho reports on preliminary results from her linguistic survey study among Finnish speakers (n=1146). The survey measured use and acceptability of traditionally gendered occupational nouns, for which a gender-neutral neologism exists (e.g., palomies/pelastaja, fireman/firefighter), as well as attitudes towards gender exclusive and inclusive language use. The participants showed a preference for gendered occupational nouns, which they generally found acceptable as well. Considering the relatively recent adoption of gender inclusive language in Finnish, the support for gendered occupational nouns is not surprising, although many participants still indicated negative attitudes towards exclusive language use.

Anna Merikallio presents their translation study that examines three science fiction stories by Ursula K. Le Guin and their translations into Finnish. It focuses on the translations of the gendered pronouns she and he in conjunction with gendered nouns (e.g. king) and adjectives with gendered connotations in descriptions of androgynous alien characters. It considers different translation strategies and their impact on overall gender representations in the stories. The results show that the commonly used translation strategies glossed over contradictions and made gender implicit, which resulted in more normative gender representations.

Speaker Bio Laura Hekanaho

Laura Hekanaho (Tampere University/University of Helsinki) is a postdoctoral researcher in linguistics. Her main area of research is language and gender research, situated in the field of sociolinguistics. In her previous studies, she has utilized survey methods, corpus methods and discourse-analytical approaches to investigate the relationship between language, gender, and identity, as well as related language attitudes and ideologies. Her PhD dissertation explored attitudes towards generic and nonbinary pronouns in English, while in her postdoctoral research she is examining gender-inclusive and exclusive language use in Finnish. Her website is: https://laurahekanaho.com/  

Speaker Bio Anna Merikallio

Anna Merikallio is a doctoral researcher in translation studies at the University of Turku. Their research focuses on nonnormative gender representations in Anglophone speculative fiction and their translations into Finnish. In their first study, Merikallio used corpus methods to inform the comparative analysis of the source and target texts to determine how translation strategies impact gender representations. Merikallio is also a professional translator, who started their own business in 2014. They have since worked both in-house and as an entrepreneur with Finnish, English and Swedish as their working languages. They live with two very helpful cats and an ever-expanding tea selection.