Publications

Cet article présente une approche de fine-tuning pour la reconnaissance automatique de la parole (RAP), qui exploite les similarités linguistiques entre dialectes afin de faire face à la rareté et au déséquilibre des données dans les langues dialectalement riches et peu dotées. Cette approche est évaluée sur l’occitan, une langue composée principalement de six variantes aux ressources inégalement réparties. Pour les dialectes les mieux dotés, le languedocien et le gascon, un fine-tuning en deux étapes est appliqué afin d’améliorer les performances de reconnaissance en tirant parti des informations interdialectales. Pour les dialectes moins représentés, nous évaluons l’efficacité d’un transfert de connaissances depuis les variantes mieux dotées, en analysant la capacité du modèle à généraliser à des dialectes faiblement représentés. Les résultats montrent que l’exploitation de la proximité linguistique entre dialectes constitue une stratégie efficace pour améliorer les performances des systèmes RAP dans des contextes à faibles ressources et à forte variabilité dialectale.

This paper presents a historical parallel corpus of languages spoken in mainland France. It consists of a collection of versions of the Parable of the Prodigal Son, collected during the 19th century. The paper aims to present the interest of such a corpus, its constitution-through XML/TEI encoding, semi-automatic alignment and projection on linguistic maps-and its potential uses for the study of these low-resource languages.

We introduce ForumOccitania, a new Occitan corpus of posts from an online forum, covering a range of topics and dialects. While some existing datasets for this low-resource language include labels of varieties within the dialect continuum, we go one step further by providing metadata pertaining to sociolinguistic factors of language variation (dialect, geographical location, age, proficiency), extracted from self-declared user profiles. We carry out statistical and qualitative analyses, as well as preliminary experiments on unsupervised dialect identification. Our results show that (i) most of the contents is written in Occitan, with the classical spelling conventions, and by young new speakers, (ii) posts display a strong presence of dialectal features from four major Occitan varieties (Lemosin, Lengadocian, Gascon, Provençau), and (iii) a simple topic modelling approach introduced by Kuparinen and Scherrer (2024) effectively detects salient features of these four varieties, but also reveals finer-grained diatopical variation tendencies.

Alsatian is a regional low-resource language spoken in a majority-language context. In order to create a voice dataset suited for training automatic speech recognition and speech-to-text models, we launched a crowdsourcing campaign on the platform Mozilla Common Voice. We describe sociolinguistic issues we ran into, such as participants’ perception of their own language and its role in the AI landscape, which are vital to address to raise the participation in the crowdsourcing effort. We found that the participants are often confused about NLP and AI tools, and have a strong interested in preserving their language.

Of the over 7,000 languages spoken in the world, commercial language identification (LID) systems only reliably identify a few hundred in written form. Research-grade systems extend this coverage under certain circumstances, but for most languages coverage remains patchy or nonexistent. This position paper argues that this situation is largely self-imposed. In particular, it arises from a persistent framing of LID as decontextualized text classification, which obscures the central role of prior probability estimation and is reinforced by institutional incentives that favor global, fixed-prior models. We argue that improving coverage for tail languages requires rethinking LID as a routing problem and developing principled ways to incorporate environmental cues that make languages locally plausible.

Automatic Text Recognition (ATR) has become a key component of digital editorial workflows, enabling the conversion of scanned documents into TEI. Beyond text recognition, ATR pipelines rely on Document Layout Analysis (DLA) to segment pages into labeled zones that support document reconstruction. Controlled vocabularies such as SegmOnto have already been widely used for this purpose, notably in projects like Gallicorpora and SETA. This paper presents LADaS (Layout Analysis Dataset with SegmOnto), an extension of SegmOnto designed for deeper alignment with the TEI Guidelines. LADaS introduces a two-level annotation system combining SegmOnto broad layout zones with visually identifiable subzones mapped on the TEI. The paper describes the process of building this controlled vocabulary and its documentation, as well as the associated annotated dataset and a proposed pipeline to convert historical scanned documents into deeper encoded TEI files.

French minority and regional languages remain under-resourced in digital formats, limiting cultural preservation and computational studies. The COLaF project develops corpora and NLP tools for French and languages spoken in France in synchrony and diachrony. This paper presents its TEI schema, which allows for the representation of linguistic variation across temporal, geographic and sociolinguistic dimensions. Using a combination of , and elements, the schema links text segments to metadata describing speakers, locations and varieties. Glottolog identifiers are used for non-standard languages. This paper advocates for the creation of a non-BCP 47-language attribute in TEI to enable the interoperability and TEI-compliance of corpora working on non-standard languages. The schema supports diverse document types from 17th-century monographs to web forums and has been applied to several corpora.

Automatic Speech Recognition (ASR) has advanced considerably in recent years, largely fueled by breakthroughs in self-supervised learning and the increasing availability of large-scale multilingual speech corpora. Models such as Whisper have demonstrated remarkable performance across numerous languages. However, despite its strong multilingual coverage, performance remains highly variable across languages. In this study, we fine-tune Whisper in four regional languages spoken in France, each selected to represent distinct linguistic and resource conditions: Basque, Occitan, Alsatian, and Shimaore. Performance is increased by fine-tuning for each language, but to significantly varying degrees. This is due to a combination of varying data quantity and quality, language similarity to an already well-covered language, and transcription standardisation: all things that low-resource languages may lack.

For decades, the pidgin-creole life cycle hypothesis was considered the standard account for the development of both pidgins and creoles. Key aspects of this account include the belief that pidgins emerge from communicative necessity in multilingual environments, while creoles are the outcomes of the stabilization of pidgins, especially via nativization. This account has been critiqued from various directions, with French-based Creoles often serving as the crux of the debate. For these languages, a major point of contention has been the similarity between the languages of the Americas and the Indian Ocean despite the apparent absence of a stable precursor pidgin. For example, McWhorter (2000) defends the life cycle model by hypothesizing that French- based Creoles ultimately descend from an unattested 17th century slave castle pidgin. In contrast, Mufwene (2020) maintains that pidgins mostly formed after the development of creoles during the during a colonial transitional period in Africa, Asia, and the Pacific. Despite these canonical debates regarding French-based Creoles, French-based pidgins remain underexplored. While Skirgård (2013) has compiled and analyzed a corpus of Français Tirailleur, a variety closely associated with West African soldiers, there is still debate about whether it represents a “real” contact variety from the late 19th and early 20th centuries Parkvall (2018) or a stereotypical projection of otherness (Vigouroux (2017). In contrast, there is more consensus that Tây Bồi, or Vietnamese Pidgin French, developed in French Indochina during roughly the same time period and fell out of use when the French military presence ended. Although Français Tirailleur and Tây Bồi share many features, they are often assumed to be mostly independent developments, and to our knowledge, no extensive comparison has been conducted. In this work, we first review descriptions of Tây Bồi and Français Tirailleur to highlight their close structural affinity, Then, we introduce textual data showing that they were largely consolidated by 1890. Finally, we revisit some contemporary accounts of language education in French colonies. Taken together, these documents suggest that, far from being spontaneous solutions to communicative barriers, Français Tirailleur and Tây Bồi were heavily shaped by top- down instruction of ostensibly simplified French. Rather than disproving the existence of pidginized varieties, the codevelopment of regionalized Frenches in West Africa and Southeast Asia underscores the contradictions and instability of thecolonial-era two-track approach to language education.