How can NLP Help Revitalize Endangered Languages? A Case Study and Roadmap for the C herokee Language (2022)

Abstract: More than 43% of the languages spoken in the world are endangered, and language loss currently occurs at an accelerated rate because of globalization and neocolonialism. Saving and revitalizing endangered languages has become very important for maintaining the cultural diversity on our planet. In this work, we focus on discussing how NLP can help revitalize endangered languages. We first suggest three principles that may help NLP practitioners to foster mutual understanding and collaboration with language communities, and we discuss three ways in which NLP can potentially assist in language education. We then take Cherokee, a severely-endangered Native American language, as a case study. After reviewing the language’s history, linguistic features, and existing resources, we (in collaboration with Cherokee community members) arrive at a few meaningful ways NLP practitioners can collaborate with community partners. We suggest two approaches to enrich the Cherokee language’s resources with machine-in-the-loop processing, and discuss several NLP tools that people from the Cherokee community have shown interest in. We hope that our work serves not only to inform the NLP community about Cherokee, but also to provide inspiration for future work on endangered languages in general.

## introduction there are an estimated 6000 to 7000 spoken languages in the world, and at least 43% of them are endangered. 2 throughout history, languages have naturally shifted and declined into dormancy. the current speed of language loss, however, is far beyond "natural". some linguists estimate that between 50% and 90% of languages will be severely endangered or dead by the end of this century @xcite . this acceleration of language endangerment owes largely to cultural, political, and economic marginalization and the rise of global imperialism. worldwide, indigenous people have suffered from colonization or conquest and given up their mother tongues in favor of another language. in order to achieve a higher social status, indigenous people have had to capitulate to colonizers' linguistic norms. following @xcite , we acknowledge that burdens such as raw material survival outweigh the more abstract concerns of maintaining a language. in other words, we cannot blame or fault indigenous people for giving up their languages in order to secure a better life under intense socioeconomic pressures. as linguists and nlp researchers, we have the responsibility to address these power imbalances and create a society where space exists for indigenous languages. moreover, language loss is memory loss, identity loss, culture loss, and knowledge loss, and it even affects the health of indigenous people @xcite . endangered languages are even more underrepresented in the nlp literature. @xcite point out that more than 88% of the world languages spoken by around 1.2 billion people are left behind, i.e., they have been and are still ignored in the aspect of language technologies. @xcite show that linguistic nlp tasks (e.g., morphology analysis) are more language inclusive than user-facing nlp tasks (e.g., machine translation). in this information age, nlp techniques are widely applied on the internet. much internet content that we are exposed to daily is processed or even created by nlp techniques. hence, the lack of nlp technology support for endangered languages reduces the degree to which users are exposed to them. unfortunately, this exacerbates the problem of linguistic marginalization, as frequent language exposure is critical to language acquisi-tion. at worst, it can generate a downward spiral: since fewer speakers create content using these languages, the scarcity of resources will in turn hinder the development of nlp technologies. on the other hand, the majority of nlp research is biased towards high-resource languages, neglects diverse linguistic typologies @xcite , and often relies on the availability of large-scale data. including endangered languages can help diagnose nlp models' generalizability @xcite and push towards universal and data-efficient approaches. in this work, we address three important steps on the roadmap of nlp for language revitalization: starting from "before nlp" to "nlp for language education" to "language-specific nlp research". before diving into nlp research, we first suggest that nlp practitioners, who are often "outsiders" of indigenous communities, become aware of three important principles: understand and respect first, decolonize research, and build a community. we especially want to promote building a community. since few people are speaking, learning, or studying an endangered language, the knowledge of each individual, the collected resources, and the developed models should be shared as widely and sustainably as possible. hence, we need a community to support this (see section 2). second, language revitalization is an attempt to reverse the decline of a language @xcite . fundamentally, this requires an increase in the number of active speakers to bring the language back to day-to-day use @xcite . due to the lack of inter-generation transmission, language education in school or online is important. we introduce three approaches for applying nlp techniques in assisting language education (section 3): automated quiz generation, automated assessment, and community-based language learning. the last approach connects to our previous point about building a community. next, we introduce the case study of cherokee; an endangered foot_2 native american language with only 2,000 fluent first-language speakers remaining. we first review its history (section 4.1) to understand how social, political, and economic repression have harmed the cherokee people and their language. then, we discuss a few linguistic distinctions of cherokee (section 4.2), including polysynthesis, word order, etc., which can help us design linguistically informed nlp models. in section 5, we review some existing high-quality cherokee resources and propose two methods to enrich resources: community-based resource collection (which also relates to our previous point of building a community) and automatic data mining. lastly, based on conversations with some cherokee speakers/researchers, we dive deep into several nlp tools that seem advantageous for community members and may be able to create new usage domains for the language, and we point out the key challenges of their development (section 6). in summary, we propose suggestions to nlp practitioners, approaches of nlp-assisted language education, and directions for cherokee language processing. we hope that our work can increase awareness of cherokee and encourage more work on minority languages. last but not the least, the authors of this work come from both the cherokee community (benjamin e. frey) and the nlp community (shiyue zhang and mohit bansal). prof. benjamin e. frey is a proficient second-language cherokee speaker and a citizen of the eastern band of cherokee indians. he has been teaching cherokee and contributing to cherokee revitalization for more than 10 years. he initiated our collaboration and continues bridging the gap between the cherokee language and language technologies. in addition, we have been talking with some other cherokee community members, including david montgomery and eva marie garroutte. prof. eva marie garroutte from boston college said: "as a citizen of the cherokee nation, i am very concerned for the preservation of my tribe's endangered language and i am convinced that dr. frey's work represents the most promising project known to me for advancing this goal." though by no means the views of this paper can represent the whole cherokee community, our proposals are strongly initiated/motivated by cherokee community members and grounded by nlp practitioners. ## before diving into nlp research we suggest nlp practitioners, who are often "outsiders" of the indigenous communities, three general principles to follow before conducting nlp research on endangered indigenous languages. understand and respect first. meaningful advances in building speech and language technologies for under-resourced languages hinge upon be-ing able to understand those languages' speaker communities and their needs. although the initial temptation among nlp researchers might be to dive in with questions about particular computational tools, that conversation cannot unfold until the speaker communities' more basic needs are met: the need for respect, reciprocity, and understanding. it may be tempting to say "this is outside the scope of our current research," yet these kinds of behaviors and assumptions are the very behaviors that led to the disenfranchisement of these groups. when we ignore someone's common humanity and assume that our need for control over the narrative and the situation is greater than their need to be seen and respected, we participate in the same marginalizing and dehumanizing behaviors that led to the problem we are purporting to address. therefore, it is instrumental that we address the cultural practices and social norms of endangered language communities before assuming we know how to position ourselves, them, and our research within their communities. ## nlp-assisted language education since little inter-generation language transmission is happening, language education is an essential requirement of language revitalization. computerassisted language learning has a long-standing history @xcite and two workshops, bea foot_3 and nlp4call foot_4 , are held for research on applying nlp for language education. here, we discuss three ways in which nlp can potentially assist language education of endangered languages. ## the cherokee language starting from this section, we illustrate the situation of endangered languages through the example of cherokee. we first review its history and linguistics. in the nlp area, we hardly get to know the languages and often let the model learn statistical patterns automatically from the data. however, it is critical to have basic knowledge of the language when contributing to its revitalization. ## cherokee language resources the availability of language resources is not only important for language education but also determines the development of nlp technologies. cherokee is categorized into "the scraping-bys" by @xcite , which means it has some amount of data but solid movements still need to be taken to increase the awareness of the language. ## nlp tools for cherokee language processing based on our conversation with a few cherokee speakers, they agree that some nlp tools are good to have and hold the potentials to be useful in cherokee language revitalization. thus, some initial attempts have been made by the cherokee language github group and us @xcite . hence, we dive deep into several specific nlp tools for cherokee language processing in this section. and for any nlp tool we develop, we want to evaluate it by the cherokee speakers, and we suggest open-sourcing it for free usage. connecting to our "build a community" proposal, we hope that nlp models can also be shared and used widely and sustainably in the community. ## conclusion & future work in this work, we discuss how nlp can help revitalize endangered languages. we first suggest general principles to nlp practitioners and propose ways of nlp-assisted language education. especially, we promote building a (online) community that support collaborative language learning, resource collection, and knowledge sharing. second, we conduct a case study for cherokee (a severelyendangered native american language). after reviewing cherokee history and linguistics, we propose two methods of enriching cherokee resources and discuss the developments of several nlp models that people from the cherokee community are interested in. we hope our work can encourage future work to think and plan the path forward for other endangered languages. in the future, we hope to broaden our collaboration to even more cherokee community members and build meaningful relationships with tribal governments, so that we can develop more useful applications through nlp techniques for supporting cherokee revitalization.