PoS-tagging a Spanish oral learner corpus

Llanos, Leonardo Campillos

doi:10.1075/scl.78.04cam

Cited by 3 publications

(1 citation statement)

References 32 publications

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“…However, POS-tagging of learner corpora has received limited attention in the literature (Picoral et al, 2021), with a prominent focus on ICLE (De Haan, 2000; Meunier and De Mönnink, 2001; Van Rooy and Schäfer, 2002, 2003), and on other corpora of L2 English (the MACLE: Malaysian corpus of learner English or Spanish ; Aziz and Don, 2019), on corpora of L2 Spanish (the CORANE corpus: Corpus para el análisis de errores de aprendices de E/LE ; Valverde Ibañez, 2011), of L2 German (the KANDEL corpus: Kansas developmental learner corpus ; Vyatkina, 2016), and of L2 French (the FLLOC corpus: French learner language oral corpora ; Marsden et al, 2002). In most of these cases, learner data were processed using taggers, tagsets and training procedures that are commonly used to process corpora of native data (Campillos Llanos, 2016).…”

Section: Pos-tagging Of the Celi Corpus: Procedures And Evaluationmentioning

confidence: 99%

The CELI corpus: Design and linguistic annotation of a new online learner corpus

Spina,

Fioravanti,

Forti

et al. 2023

Second Language Research

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This article introduces the CELI corpus, a new learner corpus of written Italian consisting of ca. 600,000 tokens, evenly distributed among CEFR (Common European Framework of Reference for Languages) proficiency levels B1, B2, C1 and C2. The collected texts derive from the language certification exams administered by the University for Foreigners of Perugia all around the world. The corpus contains rich metadata pertaining to text-related and learner-related variables. It expands the domain of learner corpora by being, among other things, both freely available online to the research community, and by focusing on a target language other than English. The article also presents and evaluates the POS-tagging procedure, thus contributing to best practices in learner corpus annotation.

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Section: Pos-tagging Of the Celi Corpus: Procedures And Evaluationmentioning

confidence: 99%

The CELI corpus: Design and linguistic annotation of a new online learner corpus

Spina,

Fioravanti,

Forti

et al. 2023

Second Language Research

View full text Add to dashboard Cite

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Spoken Spanish PoS tagging: gold standard dataset

Bonilla

2024

Lang Resources & Evaluation

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The development of a benchmark for part-of-speech (PoS) tagging of spoken dialectal European Spanish is presented, which will serve as the foundation for a future treebank. The benchmark is constructed using transcriptions of the Corpus Oral y Sonoro del Español Rural (COSER;“Audible corpus of spoken rural Spanish”) and follows the Universal Dependencies project guidelines. We describe the methodology used to create a gold standard, which serves to evaluate different state-of-the-art PoS taggers (spaCy, Stanza NLP, and UDPipe), originally trained on written data and to fine-tune and evaluate a model for spoken Spanish. It is shown that the accuracy of these taggers drops from 0.98$$-$$ - 0.99 to 0.94$$-$$ - 0.95 when tested on spoken data. Of these three taggers, the spaCy’s trf (transformers) and Stanza NLP models performed the best. Finally, the spaCy trf model is fine-tuned using our gold standard, which resulted in an accuracy of 0.98 for coarse-grained tags (UPOS) and 0.97 for fine-grained tags (FEATS). Our benchmark will enable the development of more accurate PoS taggers for spoken Spanish and facilitate the construction of a treebank for European Spanish varieties.

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Predictors of accuracy in L2 Spanish preterit-imperfect production

Minnillo,

Sánchez-Gutiérrez,

Ruiz-Alonso-Bartol

et al. 2024

IJLCR

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Few studies have considered the multitude of factors that influence learners’ accuracy of past tense-aspect use in L2 Spanish. The present study fills this gap by examining course-level, task-modality, obligatory tense-aspect, and verb frequency and regularity as predictors of English-dominant learners’ accuracy in contexts that require the Spanish preterit or imperfect. Learner narrations from the COWS-L2H and CEDEL2 corpora were analyzed. Generalized mixed-effects models reveal that obligatory tense-aspect and task-modality are significant predictors of accuracy and that frequency is only a significant predictor in imperfect-obligatory contexts for students from the same Spanish program. Data from one Spanish program is interpreted as providing partial support for the Default Past Tense Hypothesis (DPTH). The findings add complexity to our understanding of the route of preterit-imperfect acquisition, showcasing plateauing effects and highlighting students’ use of the present as a default form.

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PoS-tagging a Spanish oral learner corpus

Cited by 3 publications

References 32 publications

The CELI corpus: Design and linguistic annotation of a new online learner corpus

The CELI corpus: Design and linguistic annotation of a new online learner corpus

Spoken Spanish PoS tagging: gold standard dataset

Predictors of accuracy in L2 Spanish preterit-imperfect production

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