The Translation of Adolescence Language by means of Apertium, Systran and Google Translate

  1. Cira Napoletano, Maria
  2. Andrés Canga Alonso
Revista:
RAEL: revista electrónica de lingüística aplicada

ISSN: 1885-9089

Any de publicació: 2023

Volum: 22

Número: 1

Pàgines: 148-163

Tipus: Article

beta Ver similares en nube de resultados

Altres publicacions en: RAEL: revista electrónica de lingüística aplicada

Repositori institucional: lock_openAccés obert Editor lock_openAccés obert Editor

Resum

The present paper explores the translation of adolescents’ speech from English into Spanish using three free online translation tools (Apertium, Systran and Google Translate), and two corpora based on oral communication (the Bergen Corpus of London Teenage Language and the Linguistic Innovators Corpus). Additionally, errors were classified in terms of accuracy and fluency, and a revised version after post-editing is provided in order to overcome these mistranslations. Our findings show that the errors these Machine Translation applications produce have to do with the translation of cultural aspects, abbreviations, proper names of cities and people, as well as the loss of coherence of some extracts due to the character limit imposed by some of the tools used. Finally, emphasis is placed on the need to open new lines of research considering proverbs and idioms with a wider range of data.

Referències bibliogràfiques

  • Andersen, G. & Stenström, A. B. (1996). COLT: A progress report. ICAME Journal, 20, 133-136. Retrieved from https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=7fc6c98bc883d469a7d67b272afc770a7109b5d1
  • Baek, J. (2017, January). Introduction to terminal. In Computing in Optimization and Statistics. Lecture 1. Retrieved from/www.philchodrow.prof/cos_2017/1_terminal_and_git/Introduction%20to%20terminal.pdf
  • Brusasco, P. (2018). La traduzione automatica. Un po’ di storia: successi e qualche riflessione. Tradurre. Pratiche teorie strumenti, 14, online. Retrieved from https://rivistatradurre.it/la-traduzione-automatica/
  • Costa-Jussà, M., Farrús, M., Mariño, J. B. & Fonollosa, J. A. R. (2012). Study and comparison of rule-based and statistical Catalan-Spanish machine translation systems. Computing and Informatics, 31(2), 245-270. Retrieved from https://repositori.upf.edu/handle/10230/30925
  • Costa-Jussá, M. & Farrús, M. (2014). Towards human linguistic machine translation evaluation. Digital Scholarship in the Humanities, 30(2), 157-166. doi: 10.1093/llc/fqt065
  • Costa, Â., Ling, W., Luís, T., Correia, R. & Coheur, L. (2015). A linguistically motivated taxonomy for Machine Translation error analysis. Machine Translation, 29(2), 127-161. Retrieved from www.jstor.org/stable/44113801
  • Dias Esqueda, M. (2021). Machine translation and learning issues. Trabalhos em Linguística Aplicada, 60(1), online. doi: 10.1590/01031813932001520210212
  • Eckert, P. (2003). Language and adolescent peer groups. Journal of Language and Social Psychology, 22(1), 112-118. doi: 10.1177/0261927X02250063
  • Fernández-Torné, A. & Matamala, A. (2021). Human evaluation of three machine translation systems: From quality to attitudes by professional translators. Vigo International Journal of Applied Linguistics, 18, 97-121 doi: 10.35869/vial.v0i18.3366
  • Forcada, M. L., Tyers, F. & Ramírez Sánchez, G. (2009). The Apertium machine translation platform: Five years on. In J. A. Pérez-Ortiz, F. Sánchez-Martinez & F. M. Tyers. Proceedings of the First International Workshop on Free/Open-Source Rule-Based Machine Translation, (pp. 3-10). Alicante: University of Alicante. Retrieved from https://aclanthology.org/2009.freeopmt-1.3/
  • Forcada, M. L., Ginestí-Rosell, M., Nordfalk, J., O’Regan, J., Ortiz-Rojas, S., Pérez-Ortiz, J. A., Sánchez-Martínez, F., Ramírez-Sánchez, G. & Tyers, F. M. (2011). Apertium: A free/open-source platform for rule-based machine translation. Machine Translation, 25(2), 127-144. Retrieved from https://www.jstor.org/stable/41487458
  • Garrido Rodríguez, M. C. (2000). ¿Qué español coloquial enseñar en las clases de E/LE? In M. A. Martín Zorraquino & C. Díez Pelgrín (Eds.), Actas del XI Congreso Internacional ASELE. Zaragoza: University of Zaragoza. Retrieved from https://dialnet.unirioja.es/servlet/articulo?codigo=608273
  • Gaspari, F. & Hutchins, J. (2007). Online and free! Ten years of online machine translation: Origins, developments, current use and future prospects. In B. Maegaard (Ed.), Proceedings of Machine Translation Summit XI: Papers, Copenhagen: University of Copenhague. Retrieved from aclanthology.org/2007.mtsummit-papers.27/
  • Gaspari, F. & Zacchetta, E. (2011). Scrittura controllata per la traduzione automatica. In G. Bersani Berselli (Ed.), Usare la Traduzione Automatica (pp. 63-79). Bologna: Clueb.
  • Gouadec, D. (2010). Quality in translation. In Y. Gambier & L. Van Doorsalaer (Eds.), Handbook of Translation Studies (Vol. 1) (pp. 270-275). Amsterdam: John Benjamins.
  • Hall, D. (2020). The impersonal gets personal. Nat Lang Linguist Theory, 38, 117-150. doi: 10.1007/s11049-019-09447-w
  • Haywood, L., Thompson, M. & Hervey, S. (2009). Genre. Text type and purpose. In L. M. Haywood, M. Thompson & S. Hervey (Eds.), Thinking Spanish Translation: A Course in Translation Method: Spanish to English (2nd edition) (pp.47-67). London and New York: Routledge.
  • Hurskainen, A. (2013). Handling proper names in Machine Translation. Technical Reports in Language Technology Report, 12, online. Retrieved from https://www.academia.edu/98195885/Handling_proper_names_in_Machine_Translation
  • Hutchins, J. & Somers, H. (1992). An Introduction to Machine Translation. London: Academic Press Limited.
  • Hutchins, J. (2002). Two precursors of machine translation: Artsrouni and Trojanskij. Online. Retrieved from https://aclanthology.org/www.mt-archive.info/IJT-2004-Hutchins.pdf
  • Hutchins, J. (2003, March). Machine translation and computer-based translation tools: What’s available and how it’s used. Valladolid, University of Valladolid. Retrieved from https://www3.uji.es/~aferna/course4/MT%20process.pdf
  • Leiva Rojo, J. (2018). Aspects of human translation: The current situation and an emerging trend. Hermēneus. Revista de traducción e interpretación, 20, 257-294. doi: 10.24197/her.20.2018.257-294
  • Li, H., Graesser, A.C. & Cai, Z. (2014). Comparison of Google translation with human translation. In W. Eberle & C. Boonthum-Denecke (Eds.), Proceedings of the Twenty-Seventh International Florida Artificial Intelligence Research Society Conference (pp. 190-195). Florida: Pensacola Beach. Retrieved from https://cdn.aaai.org/ocs/7864/7864-36722-1-PB.pdf
  • Lu, R., Ali, A. M. & Ghani, C. A. A. (2021). A comparative study of corpus-based and corpus-driven approaches. Linguistics International Journal, 15(2), 119-132. Retrieved from https://connect.academics.education/index.php/lij/article/view/157
  • Marshman, E. (2023). Outside The black box: Machine Translation and the importance of what we don’t know. Canada: University of Ottawa. Retrieved from https://dhsiteorg.files.wordpress.com/2023/02/marshman_dht2023.pdf
  • Molina, L. & Hurtado Albir, A. (2002). Translation techniques revisited: A dynamic and functionalist approach. Meta XLVII, 4, 499-500. doi: 10.7202/008033ar
  • Muftah, M. (2022). Machine vs Human Translation: a new reality or a threat to professional Arabic-English translators. PSU Research Review, online. doi: 10.1108/PRR-02-2022-0024
  • Palacios Martínez, I. M. (2010). The expression of negation in British teenagers’ language: A preliminary study. Journal of English Linguistics, 39(1), 4-35. doi: 10.1177/0075424210366905
  • Palacios Martínez, I. M. (2011). The language of British teenagers: A preliminary study of its main grammatical features. Atlantis, 33(1), 105-126. Retrieved from https://minerva.usc.es/xmlui/bitstream/handle/10347/21543/1/2011_atlantis_palacios_language.pdf
  • Palacios Martínez, I. M. (2013). Non-standard negation in Modern English: A corpus-based study of four salient features. ES Review. Spanish Journal of English Studies, (34), 211-226. Retrieved from https://revistas.uva.es/index.php/esreview/article/view/2183
  • Palacios Martínez, I. M. (2018). ʻHelp me move to that, bloodʼ, A corpus-based study of the syntax and pragmatics of vocatives in the language of British teenagers. Journal of Pragmatics, 130(4), 33-50. doi: 10.1016/j.pragma.2018.04.001
  • Palacios Martínez I. M. (2021). Recent changes in London English: An overview of the main lexical, grammar and discourse features of Multicultural London English (MLE). Complutense Journal of English Studies, 29, 1-20. doi: 10.5209/cjes.77504
  • Popović, M. (2020). Relations between comprehensibility and adequacy errors in machine translation output. In R. Fernández & T. Linzen (Eds.), Proceedings of the 24th Conference on Computational Natural Language Learning (pp. 256-264). Online version: The Association for Computational Linguistics. Retrieved from https://aclanthology.org/2020.conll-1.19/
  • Pym, A. (2020). Quality. In M. O’Hagan (Ed.), The Routledge Handbook of Translation and Technology (pp. 437-449). New York: Routledge.
  • Rahm, E. & Hai Do, H. (2000). Data cleaning: Problems and current approaches. IEEE Data Eng. Bull, 23, 3-13. Retrieved from https://dbs.uni-leipzig.de/research/publications/data-cleaning-problems-and-current-approaches
  • Sharma, S., Diwakar, M., Singh, P., Singh, V., Kadry, S. & Kim, J. (2023). Machine translation systems based on classical-statistical-deep learning approaches. Electronics, 12(7), 1716. doi: 10.3390/electronics12071716
  • Sharou, K. A. & Specia, L. (2022). A taxonomy and study of critical errors in Machine Translation. In H. Moniz, L. Macken. A. Rufener, L. Barrault, M. R. Costa-jussà, C. Declercq, M. Koponen, E. Kemp, S. Pilos, M. L. Forcada, C. Scarton, J. Van den Bogaert, J. Daems, A. Tezcan, B. Vanroy & M. Fonteyne (Eds.), Proceedings of the 23rd Annual Conference of the European Association for Machine Translation (pp. 171-180). Ghent: Ghent University. Retrieved from https://aclanthology.org/2022.eamt-1.20/
  • Storjohann, P. (2005). Corpus-driven vs. corpus-based approach to the study of relational patterns. In University of Birmingham (Ed.), Proceedings of the Corpus Linguistics Conference 2005 (pp. online). Birmingham: University of Birmingham. Retrieved from https://ids-pub.bsz-bw.de/frontdoor/deliver/index/docId/5006/file/Storjohann_Corpus_driven_vs_corpus_based_ approach_to_the_study_of_relational_patterns_2005.pdf
  • Suárez González, I. (2022). Una aproximación a la anticortesía y su explotación didáctica en el aula de ELE. Foro de profesores de E/LE, 18, 199-229. doi: 10.7203/foroele.18.25311
  • Tagliamonte, S. A. (2016). Teen Talk. The Language of Adolescents. Cambridge: University of Cambridge.
  • Tavosanis, M. (2019). Valutazione umana di Google Traduttore e DeepL per le traduzioni di testi giornalistici dall’inglese verso l’italiano. In R. Bernardi, R. Navigli & G. Semeraro (Eds.), CLiC-it 2019. Proceedings of the Sixth Italian Conference on Computational Linguistics (pp.1-7). Retrieved from https://ceur-ws.org/Vol-2481/paper70.pdf
  • Thiruumeni, P.G., Anand, K., Dhanalakshmi, V. & Soman, K.P. (2011). An approach to handle idioms and phrasal verbs in English-Tamil Machine Translation system. International Journal of Computer Applications, 26, 36-41. doi: 10.5120/3139-4328
  • Torgersen, E. N., Gabrielatos, C., Hoffmann, S. & Fox, S. (2011). A corpus-based study of pragmatic markers in London English. Corpus Linguistics and Linguistic Theory, 7(1), 93-118. doi: 10.1515/cllt.2011.005
  • Vela-Valido, J. (2021). Translation quality management in the AI age. New technologies to perform translation quality management operations. Revista Tradumàtica. Tecnologies de la Traducció, 19, 93-111. doi: 10.5565/rev/tradumatica.285
  • Vieira, L. N. (2020). Post-editing of machine translation. In M. O’Hagan (Ed.), The Routledge Handbook of Translation and Technology (pp. 319-331). New York: Routledge.
  • Vinay, J. P. & Darbelnet, J. (1995). Comparative Stylistics of French and English: A Methodology for Translation. Amsterdam: John Benjamins.
  • Webster, R., Fonteyne, M., Tezcan, A., Macken, L. & Daems, J. (2020). Gutenberg goes neural: Comparing features of Dutch human translations with Raw Neural Machine Translation outputs in a corpus of English literary classics. Informatics, 7(32), online. doi: 10.3390/informatics7030032
  • Yang, J. & Croiset, T. (2009). SYSTRAN Chinese-English and English-Chinese Hybrid Machine Translation Systems. Retrieved from aclanthology.org/www.mt-archive.info/CWMT-2009-Yang.pdf
  • Zhao, L. (2022). The relationship between Machine Translation and Human Translation under the influence of Artificial Intelligence Machine Translation. Mobile Information Systems, 5, 1-8. doi: 10.1155/2022/9121636