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        <title>Child Support: Leveraging Lexifiers Resources to Support Creoles ASR</title>
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        <namePart type="given">Éric</namePart>
        <namePart type="family">Le Ferrand</namePart>
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    <name type="personal">
        <namePart type="given">Fabiola</namePart>
        <namePart type="family">Henri</namePart>
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        <dateIssued>2026-07</dateIssued>
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            <title>Proceedings of the Ninth Workshop on the Use of Computational Methods in the Study of Endangered Languages (ComputEL-9)</title>
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        <name type="personal">
            <namePart type="given">Godfred</namePart>
            <namePart type="family">Agyapong</namePart>
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        <name type="personal">
            <namePart type="given">Sarah</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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            <namePart type="given">Antti</namePart>
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            <namePart type="given">Ali</namePart>
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    <abstract>Creole languages emerged from colonial contact and the slave trade. Although they inheritthe bulk of their vocabulary from a “lexifier”language, they remain classic low-resourcelanguages, presenting significant challengesfor speech technology. This paper exploreshow the abundant resources of a lexifier canbe leveraged for Creole-specific tools, focusing on Automatic Speech Recognition (ASR).Specifically, we use an artificial dataset generated a French-trained Text-to-Speech (TTS)model and French datasets to pre-finetune ASRmodels for two French-based Creoles. Ourresults demonstrate that a two-stage trainingsetup where models are first trained on artificial datasets leads to substantial performanceboost for transcribing Creole languages. Additionally, this approach serves as a viable firststep for ASR development in zero-resource scenarios.</abstract>
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        <url>https://aclanthology.org/2026.computel-1.12/</url>
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            <start>111</start>
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%0 Conference Proceedings
%T Child Support: Leveraging Lexifiers Resources to Support Creoles ASR
%A Le Ferrand, Éric
%A Henri, Fabiola
%Y Agyapong, Godfred
%Y Moeller, Sarah
%Y Arppe, Antti
%Y Marashian, Ali
%Y Rosenblum, Daisy
%S Proceedings of the Ninth Workshop on the Use of Computational Methods in the Study of Endangered Languages (ComputEL-9)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, USA
%@ 979-8-89176-422-4
%F le-ferrand-henri-2026-child
%X Creole languages emerged from colonial contact and the slave trade. Although they inheritthe bulk of their vocabulary from a “lexifier”language, they remain classic low-resourcelanguages, presenting significant challengesfor speech technology. This paper exploreshow the abundant resources of a lexifier canbe leveraged for Creole-specific tools, focusing on Automatic Speech Recognition (ASR).Specifically, we use an artificial dataset generated a French-trained Text-to-Speech (TTS)model and French datasets to pre-finetune ASRmodels for two French-based Creoles. Ourresults demonstrate that a two-stage trainingsetup where models are first trained on artificial datasets leads to substantial performanceboost for transcribing Creole languages. Additionally, this approach serves as a viable firststep for ASR development in zero-resource scenarios.
%U https://aclanthology.org/2026.computel-1.12/
%P 111-117

Markdown (Informal)

[Child Support: Leveraging Lexifiers Resources to Support Creoles ASR](https://aclanthology.org/2026.computel-1.12/) (Le Ferrand & Henri, ComputEL 2026)

• Child Support: Leveraging Lexifiers Resources to Support Creoles ASR (Le Ferrand & Henri, ComputEL 2026)

ACL

• Éric Le Ferrand and Fabiola Henri. 2026. Child Support: Leveraging Lexifiers Resources to Support Creoles ASR. In Proceedings of the Ninth Workshop on the Use of Computational Methods in the Study of Endangered Languages (ComputEL-9), pages 111–117, San Diego, California, USA. Association for Computational Linguistics.