Grammar Assistance Using Syntactic Structures (GAUSS)
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arXiv
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| Format: | Preprint |
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2024
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| author | Zamaraeva, Olga Allegue, Lorena S. Gómez-Rodríguez, Carlos Ogneva, Anastasiia Alonso-Ramos, Margarita |
| author_facet | Zamaraeva, Olga Allegue, Lorena S. Gómez-Rodríguez, Carlos Ogneva, Anastasiia Alonso-Ramos, Margarita |
| contents | Automatic grammar coaching serves an important purpose of advising on standard grammar varieties while not imposing social pressures or reinforcing established social roles. Such systems already exist but most of them are for English and few of them offer meaningful feedback. Furthermore, they typically rely completely on neural methods and require huge computational resources which most of the world cannot afford. We propose a grammar coaching system for Spanish that relies on (i) a rich linguistic formalism capable of giving informative feedback; and (ii) a faster parsing algorithm which makes using this formalism practical in a real-world application. The approach is feasible for any language for which there is a computerized grammar and is less reliant on expensive and environmentally costly neural methods. We seek to contribute to Greener AI and to address global education challenges by raising the standards of inclusivity and engagement in grammar coaching. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_18340 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Grammar Assistance Using Syntactic Structures (GAUSS) Zamaraeva, Olga Allegue, Lorena S. Gómez-Rodríguez, Carlos Ogneva, Anastasiia Alonso-Ramos, Margarita Computation and Language Automatic grammar coaching serves an important purpose of advising on standard grammar varieties while not imposing social pressures or reinforcing established social roles. Such systems already exist but most of them are for English and few of them offer meaningful feedback. Furthermore, they typically rely completely on neural methods and require huge computational resources which most of the world cannot afford. We propose a grammar coaching system for Spanish that relies on (i) a rich linguistic formalism capable of giving informative feedback; and (ii) a faster parsing algorithm which makes using this formalism practical in a real-world application. The approach is feasible for any language for which there is a computerized grammar and is less reliant on expensive and environmentally costly neural methods. We seek to contribute to Greener AI and to address global education challenges by raising the standards of inclusivity and engagement in grammar coaching. |
| title | Grammar Assistance Using Syntactic Structures (GAUSS) |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2406.18340 |