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Titel: Dialogue Pidgin Text Adaptation via Contrastive Fine-Tuning
VerfasserIn: Chang, Ernie
Alabi, Jesujoba O.
Adelani, David Ifeoluwa
Demberg, Vera
Sprache: Englisch
Titel: 3rd Workshop on African Natural Language Processing (AfricaNLP 2022)
Seiten: 1-8
Erscheinungsjahr: 2022
Konferenzort: Online
Freie Schlagwörter: pidgin
language generation
dialogue
multilingual
DDC-Sachgruppe: 400 Sprache, Linguistik
Dokumenttyp: Konferenzbeitrag (in einem Konferenzband / InProceedings erschienener Beitrag)
Abstract: The surging demand for multilingual dialogue systems often requires a costly labeling process for each language addition. For low resource languages, human annotators are continuously tasked with the adaptation of resource-rich language utterances for each new domain. However, this prohibitive and impractical process can often be a bottleneck for low resource languages that are still without proper translation systems nor parallel corpus. In particular, it is difficult to obtain task-specific low resource language annotations for the English-derived creoles (e.g. Nigerian and Cameroonian Pidgin). To address this issue, we utilize the pretrained language models i.e. BART which has shown great potential in language generation/understanding – we propose to finetune the BART model to generate utterances in Pidgin by leveraging the proximity of the source and target languages, and utilizing positive and negative examples in contrastive training objectives. We collected and released the first parallel Pidgin-English conversation corpus in two dialogue domains and showed that this simple and effective technique is sufficient to yield impressive results for English-to-Pidgin generation, which are two closely-related languages.
URL der Erstveröffentlichung: https://openreview.net/pdf?id=HAzG99MV8-5
Link zu diesem Datensatz: urn:nbn:de:bsz:291--ds-408761
hdl:20.500.11880/36718
http://dx.doi.org/10.22028/D291-40876
Datum des Eintrags: 27-Okt-2023
Fakultät: MI - Fakultät für Mathematik und Informatik
Fachrichtung: MI - Informatik
Professur: MI - Prof. Dr. Vera Demberg
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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