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# A Hiking Path for Burgenland Croatian

Stephanie Cajka, Mélanie Jouitteau, Eva Vetter

► To cite this version:

Stephanie Cajka, Mélanie Jouitteau, Eva Vetter. A Hiking Path for Burgenland Croatian. Eurocall, Aug 2025, Milan, Italy. hal-05385510

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https://hal.science/hal-05385510v1

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Distributed under a Creative Commons Attribution 4.0 International License
# A Hiking Path for Burgenland Croatian

## Desirability and technical affordances of AI language learning chatbots for minoritised languages: a pilot study

Stefanie Cajka | University of Vienna | stefanie.cajka@univie.ac.at

Mélanie Jouitteau | IKER, CNRS | melanie.jouitteau@iker.cnrs.fr

Eva Vetter | University of Vienna | eva.vetter@univie.ac.at

EUROCALL 2025

29 August 2025

MINDS & SPARKS

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UNIVERSITY
OF TARTU

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universität
wien

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ESPRONCEDA
INSTITUTE OF ART & CULTURE

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NUROGAMES

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SOAS
University of London

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University of
Boehampton
London

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Funded by
the European Union

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or European Research Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.

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### RISE UP Project

**Programme**

Horizon Europe

**Project Type**

Coordination and Support Action

**Project duration**

36 months (01/02/2023 – 31/01/2026)

**Partners**

8 from 6 countries

**Budget**

1,872,192.00 € (EU contribution)

### Entrelangues

**Project Type**

Coordination and Documentation

**Project duration**

(2013 – now)

**Partners**

French National Research Center (CNRS)
IKER, UMR 5478 & MODYCO, UMR 7114)

**Budget**

(Public, French)
## Selected Language Community

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Burgenland Croatian / gradišćanskohrvatski
* **16th century:** settlers came from Croatia to the area of today's eastern Austria (Burgenland and Lower Austria), Slovakia, Hungary and the Czech Republic

* **Burgenland Croatian communities in**

* Austria: Burgenland (easternmost province) + Vienna

* Hungary

* Slovakia

* Czech Republic

* Approx. up to **65.000 speakers** overall

(Tyran 2022a)

<figure><img src="image_14.png" /><figcaption>Settlement of Burgenland Croats / Villages with Croatian-Speaking Population.</figcaption></figure>

Note. Adapted from Pavetich (2020), compiled for this dossier.

(Tyran 2022b: 6)
* The **Burgenland Croatian community** is

* one of six **autochthonous minorities** in Austria

* protected under the **Framework Convention for the Protection of National Minorities** (FCN M 1995)

* Exposed to **assimilation pressure** → led to the assimilation of the population in Lower Austria in the 18th and 19th century (Tyran 2022a)

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* The **Burgenland Croatian language** is

* **official language** in six of the seven districts of Burgenland

* protected under the **European Charter for Regional or Minority Languages** (Charter RML 1992)

* classified as **"threatened"** (EGIDS (**Lewis & Simons 2010**)) and **"endangered/unsafe"** (WAL (UNESCO 2021))

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In this paper,

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we provide evidence for the **social desirability of AI tools** for Burgenland Croatian in Austria

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we inventory **NLP resources for Burgenland Croatian**, take stock of the **challenges** we encounter and propose **solutions** to be suggested to the community

with the aim to

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highlight the **relevance of AI tools** for minoritised languages and

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raise awareness about the **importance of research and development** in this regard.
ARTICLE 2

Everyone is entitled to all the rights and freedoms set forth in this Declaration, without distinction of any kind, such as race, colour, sex, language, religion, political or other opinion, national or social origin, property, birth or other status.

General Assembly resolution 217 A
([https://docs.un.org/en/A/RES/217(III)]())
Cultural Heritage
and Identity

(Grenoble 2021; McCarty 2021)

It's good for
everyone!

Wellbeing

(Grenoble & Whaley 2021; Whalen
& al. 2016 ; Hallett & al. 2007)

Social Justice

(McCarty 2021; Skutnabb-Kangas
& Phillipson 1994)

Safeguarding
Knowledge

(Grenoble 2021; Meighan 2022)

Scientific Value

(Himmelmann 2006, Nevins 2025)
<table><thead><tr><td>Potentials</td><td>Why is it relevant?<br>(Based on fieldwork conducted in RISE UP)</td></tr></thead><tbody><tr><td>Availability of language learning possibilities</td><td>Possibilities and materials for language learning are often not available or hardly accessible in minoritised language contexts</td></tr></tbody></table>
Minoritised Language Learning with AI tools

<table><thead><tr><td>Potentials</td><td>Why is it relevant?<br>(Based on fieldwork conducted in RISE UP)</td></tr></thead><tbody><tr><td>Availability of language learning possibilities</td><td>Possibilities and materials for language learning are often not available or hardly accessible in minoritised language contexts</td></tr><tr><td>Personalised learning experience (<a href="#">Creely 2024</a>)</td><td>Learner groups in minoritised language contexts can be small and heterogeneous</td></tr></tbody></table>
<table><thead><tr><td>Potentials</td><td>Why is it relevant?<br>(Based on fieldwork conducted in RISE UP)</td></tr></thead><tbody><tr><td>Availability of language learning possibilities</td><td>Possibilities and materials for language learning are often not available or hardly accessible in minoritised language contexts</td></tr><tr><td>Personalised learning experience (<a href="https://creely2024.com">Creely 2024</a>)</td><td>Learner groups in minoritised language contexts can be small and heterogeneous</td></tr><tr><td>Offering a conversation partner</td><td>Scarcity of human conversation partners and possibilities for real-life interactions in minoritised languages</td></tr></tbody></table>
# Minoritised Language Learning with AI tools

<table><thead><tr><td>Potentials</td><td>Why is it relevant?<br>(Based on fieldwork conducted in RISE UP)</td></tr></thead><tbody><tr><td>Availability of language learning possibilities</td><td>Possibilities and materials for language learning are often not available or hardly accessible in minoritised language contexts</td></tr><tr><td>Personalised learning experience (<a href="https://creely2024.com">Creely 2024</a>)</td><td>Learner groups in minoritised language contexts can be small and heterogeneous</td></tr><tr><td>Offering a conversation partner</td><td>Scarcity of human conversation partners and possibilities for real-life interactions in minoritised languages</td></tr><tr><td>Can serve as a linguistic safe space</td><td>Using a minoritised language can go along with discrimination</td></tr></tbody></table>
<table><thead><tr><td>Potentials</td><td>Why is it relevant?<br>(Based on fieldwork conducted in RISE UP)</td></tr></thead><tbody><tr><td>Availability of language learning possibilities</td><td>Possibilities and materials for language learning are often not available or hardly accessible in minoritised language contexts</td></tr><tr><td>Personalised learning experience (<a href="#">Creely 2024</a>)</td><td>Learner groups in minoritised language contexts can be small and heterogeneous</td></tr><tr><td>Offering a conversation partner</td><td>Scarcity of human conversation partners and possibilities for real-life interactions in minoritised languages</td></tr><tr><td>Can serve as a linguistic safe space</td><td>Using a minoritised language can go along with discrimination</td></tr><tr><td>Rapid responses and interactive content (<a href="#">Creely 2024</a>); potential positive impacts on learning motivation, engagement, autonomy</td><td>That's assumed to be beneficial for language learning in general 😊</td></tr></tbody></table>
RISE UP Survey

* Five versions → one for each RISE UP case study community

* Translated into more than 15 language varieties

* Online survey in Microsoft Forms

* 68 questions

* Released in spring 2024
RISE UP Survey: BC

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121 questionnaires

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10-17: 0.0%

18-29: 25.6%

30-49: 35.5%

50-69: 28.9%

70 or older: 9.9%

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Female: 60.3%

Male: 36.4%

Non-binary: 0.0%

Prefer not to disclose: 3.3%

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Primary school: 0.0%

Secondary school: 18.2%

Vocational training: 6.6%

Higher education: 75.2%
RISE UP Survey: BC

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121 questionnaires

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10-17: 0.0%

18-29: 25.6%

30-49: 35.5%

50-69: 28.9%

70 or older: 9.9%

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Female: 60.3%

Male: 36.4%

Non-binary: 0.0%

Prefer not to disclose: 3.3%

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Primary school: 0.0%

Secondary school: 18.2%

Vocational training: 6.6%

Higher education: 75.2%

Interviews

- Two qualitative semi-structured guideline interviews

- Conducted with speakers of Burgenland Croatian

- Work in progress
How important is it to you that the following digital tools or services are available in Burgenland Croatian? - Chatbots (e.g., ChatGPT, Bard)
(n=121)

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Discussing ChatGPT's (4o) functionality in Burgenland Croatian

Ja, also es ist, man kann es auf jeden Fall verstehen. Es ist halt jetzt nicht unbedingt richtig, aber es ist an manchen Stellen nicht schlecht. IBK2, 14:59-15:14

Yes, well, it's definitely understandable. It's not necessarily correct, but some parts aren't bad.
## Discussing the desirability of an AI chatbot in Burgenland Croatian

Naja, des wär für unsere Sprache schon was ganz Tolles, weil alle Sprachen, also die großen Sprachen, bieten es an, nicht? Und vor allem a, wenn man so, die Zeit bringt es einfach mit sich, dass man sich mit dem jetzt a befassen muss [...]. Und wenn jetzt natürlich das in der burgenländischkroatischen Sprache zurückbleibt, ist das halt wieder so ein bissl ein Zeichen, so veraltet und nicht lebendig und ja, ned modern. Ja.

[...]

Und auch a Möglichkeit, das Sterben der Sprache weiter hinauszuzögern. (Oder?) Man (lachen) weiß nicht, ob ma es verhindern können, aber halt, ja. IBK1, 01:24-02:06; 07:44-07:55

Well, that would be great for our language, because all languages, the major languages, offer it, don't they? And especially when you consider that the times simply demand that we address this issue now [...]. And if this is now left behind in the Burgenland Croatian language, it's just another sign that it's outdated and not alive and, yes, not modern. Yes.

[...]

And also a way to further delay the death of the language, (isn't it?). One (laughing) doesn't know if one can prevent it, but still, yes.
Discussing the desirability of an AI chatbot in Burgenland Croatian

Ja, sicher gibt es Vorteile. Es ist einfach so, es gibt ja viel zu wenig Angebot. Es gibt viel weniger Kurse als Interesse. Das sieht man/ Ich kenne so viele Kurse, die nicht zustande kommen sind, weil es keine Lehrperson gibt. Es gäbe sicher auch Leute, die halt vielleicht einfach nur sich das kurz anschauen wollen, nicht vielleicht gleich hier den ganzen Kurs besuchen. Dann ist sowas natürlich praktisch.

IBK2, 21:47-22:15

Yes, there are definitely advantages. It's just that there aren't enough courses on offer. There are far fewer courses than there is interest. You can see that. I know of so many courses that don't happen because there are no teachers. There are certainly people who just want to take a quick look, rather than attending the whole course. Then something like this is obviously practical.
## Required focus on spoken language

Es müsste eine gesprochene Komponente geben. Und diese gesprochene Komponente müsste tatsächlich auf unterschiedlichen Varietäten sprechen können.

IBK2, 19:40-19:52

There would have to be a spoken component. And this spoken component would actually have to be able to speak in different varieties.

Des ist schon, also so sprechen, das wäre super, ne, sprechen, aber schreiben ist, glaube ich scho so bissl a Hemmschwelle. Dass das gar nicht genutzt werden würde, ja.

IBK1, 23:24-23:38

Talking would be great, but writing is a bit of a barrier, I think. That it wouldn't be used at all, yes.
An Example of Desirability: ČaBot

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ČaBot

Von Vivien Mileder

Vježba s dicom govoriti gradišćanskohrvatski. Übt mit Volksschulkindern das Sprechen auf Burgenlandkroatisch. WICHTIG-VAŽNO: Für die Nutzung durch Kinder NUR unter Aufsicht!

Link: https://chatgpt.com/g/g-679259f04b208191b601c542539c01d2-cabot

→ Is a GPT

→ Not maintained

→ OpenAI copyright
Joshi et al 2020: 6284-6285

- **Green (0):** ignored with regards to language technologies; virtually no unlabeled data

- **Blue (1):** some unlabeled data

- **Purple (2):** small sets of labeled datasets; efforts to “keep them alive in the digital world”

- **Yellow (3):** language with a thriving cultural online community; unsupervised pre-training; however: insufficient efforts in labeled data collection

- **Orange (4):** large among of unlabeled data; lesser amount of labeled data

- **Red (5):** dominant online presence

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**Joshi et al 2020: 6284-6285**

Burgenland Croatian

* **Green (0):** ignored with regards to language technologies; virtually no unlabeled data

* **Blue (1):** some unlabeled data

* **Purple (2):** small sets of labeled datasets; efforts to “keep them alive in the digital world”

* **Yellow (3):** language with a thriving cultural online community; unsupervised pre-training; however: insufficient efforts in labeled data collection

* **Orange (4):** large among of unlabeled data; lesser amount of labeled data

* **Red (5):** dominant online presence

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RISE UP has inventoried human ready corpora in Burgenland Croatian:

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There are also **NLP ready corpora** (29 minutes of aligned data):

* Example: Breu, W., & Scholze, L. (2013). *Le mariage en Burgenland*. https://doi.org/10.34847/COCOON.FB702BA6-4A17-3FD9-8326-64E0288FCF27 → Copyright (c) Breu, Walter, CC BY-NC 2.5:

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* An AI model could be trained with a **typologically close variety**, and then **fine-tuned with Burgenland Croatian** data

* The typologically closest language would be the **Chakavian dialect** of Croatian, **however**: also low resource (and diachronic divergences)

* **Croatian** is typologically the closest pillar → available on Google Translate, has a large Wikipedia (408,000 pages in June 2025), and 86,137,615 pair sentences with English in **OPUS**
# A Hiking Path to a Multimodal Chatbot

<figure><img src="image_38.png" /></figure>

Multimodal
Chatbot
# A Hiking Path to a Multimodal Chatbot

<figure><img src="image_39.png" /></figure>

Multimodal
Chatbot

Translation
# A Hiking Path to a Multimodal Chatbot

<figure><img src="image_40.png" /></figure>

Translated material
(written texts, lexicons,
oral translations)
# A Hiking Path to a Multimodal Chatbot

<figure><img src="image_41.png" /></figure>
# A Hiking Path to a Multimodal Chatbot

<figure><img src="image_42.png" /></figure>

Transcribed audio material
(200h, diversity of voices,
natural)
# A Hiking Path to a Multimodal Chatbot

<figure><img src="image_43.png" /></figure>
# A Hiking Path to a Multimodal Chatbot

<figure><img src="image_44.png" /></figure>

Read material
(50h, very clean sound)
# A Hiking Path to a Multimodal Chatbot

<figure><img src="image_45.png" /></figure>

## Data has to be

* human gold quality

* under a copyright
suitable for AI training
# A Hiking Path to a Multimodal Chatbot

<figure><img src="image_46.png" /></figure>
# A Hiking Path to a Multimodal Chatbot

<figure><img src="image_47.png" /></figure>

Sizable raw material (e.g., wiki), curated scraped material
* Latin alphabet

* Small corpora freely available (29 minutes)

* Translations carried out in the private sector

Some data available in Burgenland Croatian:

* Translated text on YouTube: https://www.youtube.com/watch?v=L3vs8f-Ncdo

* Quite well-known recipe blog, not transcribed in Burgenland Croatian, but translated into German: https://www.youtube.com/watch?v=1lmt8dkr3ZQ&t=205s

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* Needs **natural spoken data with transcription**

* On Common Voice, Serbian is typologically the closest, with only 9 hours

* Examples for natural spoken data in Burgenland Croatian (without transcriptions though):

* Autobiographical narration (18 interviews, each 1-2 hours), one example: http://www.forschungsgesellschaft.at/testimonium/jordanich/jordanich_hr.php

* Reading of children's books, one example: https://www.youtube.com/watch?v=nBgHfM99vyg

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* Multilingual TTS are getting better (Lux & al. 2024)

* On a Low-resource language like Breton, 10 native speakers graded 200 sentences and gave it 4 out of 5 (1=foreigner with no training, 5=native like speech)

* A starting goal could be **50 cleanly recorded hours of reading in Burgenland Croatian;** with the same voices also reading in their other language (building of bilingual voices) as an addition

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* In Europe, data mining is allowed for scientific entities and cultural heritage institutions (2019/790)

* However: Burgenland Croatian has no digital identification yet (ISO 639-2) → low automatic findability

* (sla = slavic, hbs = Serbo-Croatian, hrv = Croatian)
* Preparing an application for the obtention of an ISO 639 code for Burgenland Croatian

→ would allow to open a set for Burgenland Croatian on Common Voice

→ would facilitate scraping

* Invest in a small engineering project for a language recogniser

* Relying on crowdsourcing with a deposit campaign on Zenodo

* Ideas for translation

→ A community tailored digital tool could collect aligned pairs of sentences, for example as a school exercise

→ Microsoft Translator asked 250,000 parallel sentences for inclusion of Lower Sorbian into the Microsoft suite. The corpus was constituted by professionals, 1€/sentence pair.

* Explore the potential of copyright-free audio data from podcasts, videos, etc.
## What can the role of us (researchers) be in that process?

* Facilitators and bridge builders with a community-centered perspective

## What can we do?

* Raise awareness in the community about the NLP need for the resources that they already develop, and explain how to make it count for digital development

* Building bridges between communities and developers

* Point to relevant principles and laws, e.g. FAIR principles or copyright laws concerning AI

* Make community resources (more) visible; both for humans and machines

* Organise funding to facilitate efforts in this regard
Charter RML. 1992. *European Charter for Regional or Minority Languages: Strasbourg 5.XI.1992*. Online document: https://rm.coe.int/1680695175 (07.07.2025).

Creely, Edwin. 2024. Exploring the Role of Generative AI in Enhancing Language Learning:Opportunities and Challenges. International Journal of Changes in Education 1(3), 158–167. https://doi.org/10.47852/bonviewIJCE42022495

FCNM. 1995. Framework Convention for the Protection of National Minorities: Strasbourg 1.II.1995. Online document: https://rm.coe.int/168007cdac (07.07.2025).

Grenoble, Leonore. A. 2021. Endangered Languages and Well-Being. In Justyna Olko & Julia Sallabank (Eds.), Revitalizing Endangered Languages: A Practical Guide. 9-22. Cambridge: Cambridge University Press.

Grenoble, Lenore A. & Lindsay J. Whaley. 2021. Toward a new conceptualisation of language revitalisation, Journal of Multilingual and Multicultural Development, 42:10, 911-926 https://doi.org/10.1080/01434632.2020.1827645

GoFair. N. d. FAIR Principler. https://www.go-fair.org/fair-principles/

Hallett, D., M. J. Chandler, and C. E. Lalonde. 2007. "Aboriginal Language Knowledge and Youth Suicide." Cognitive Development 22 (3): 392–399. text

Himmelmann, Nikolaus P. 2006. Language documentation: What is it and what is it good for? In Jost Gippert, Nikolaus P. Himmelmann & Ulrike Mosel (Eds.), Essentials of Language Documentation 1-30. Berlin, New York: Mouton de Gruyter. text
Jouitteau, Mélanie. 2023d. 'Guide de survie des langues minorisées à l'heure de l'intelligence artificielle : Appel aux communautés parlantes', *Lapurdum*, numéro spécial 6, **text**.

Jouitteau, Mélanie. 2024a. 'AI is coming and our languages need to catch the wave', Gareth Watkins (éd.), addendum to *Language and Technology in Wales* 2, U. Bangor, 66-72, **text**.

Lewis, M. P. & Simons, G. F.. 2010. Assessing endangerment: Expanding Fishman's GIDS. *Revue Roumaine de Linguistique* 55(2). 103-120. **Text**.

Lux, Florian, Sarina Meyer, Lyonel Behringer, Frank Zalkow, Phat Do, Matt Coler, Emanuel A. P. Habets, Ngoc Thang Vu. 2024. 'Meta Learning Text-to-Speech Synthesis in over 7000 Languages', "Interspeech" 2024, 1-5 September 2024, Kos, Greece, **text**.

McCarty, Teresa L. 2021. The holistic benefits of education for Indigenous language revitalisation and reclamation (ELR2), *Journal of Multilingual and Multicultural Development*, 42:10, 927-940, DOI: 10.1080/01434632.2020.1827647.

Meighan, Paul J. 2022. "Indigenous Language Revitalization Using *TEK-Nology*: How Can Traditional Ecological Knowledge (TEK) and Technology Support Intergenerational Language Transmission?" *Journal of Multilingual and Multicultural Development* 45 (8): 3059-77. doi:10.1080/01434632.2022.2084548.

Nevins, Andrew. 2022. When Minoritized Languages Change Linguistic Theory, Cambridge University Press, **text**.
Skutnabb-Kangas, Tove and Phillipson, Robert. *Linguistic Human Rights: Overcoming Linguistic Discrimination*, Berlin, New York: De Gruyter Mouton, 1994. https://doi-org.uaccess.univie.ac.at/10.1515/9783110866391

Tyran, Katharina. 2022a. Zur Situation der kroatischen Volksgruppe und ihrer Sprache in Österreich. Europäisches Journal für Minderheitenfragen 15(3-4), 241-260. **Text.**

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Let's stay in touch:

Stefanie Cajka: [stefanie.cajka@univie.ac.at](mailto:stefanie.cajka@univie.ac.at)

Mélanie Jouitteau: [melanie.jouitteau@iker.cnrs.fr](mailto:melanie.jouitteau@iker.cnrs.fr)

Eva Vetter: [eva.vetter@univie.ac.at](mailto:eva.vetter@univie.ac.at)

Find out more about RISE UP:

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SCAN ME

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