Chinese–Spanish neural machine translation enhanced with character and word bitmap fonts

Recently, machine translation systems based on neural networks have reached state-of-the-art results for some pairs of languages (e.g., German–English). In this paper, we are investigating the performance of neural machine translation in Chinese–Spanish, which is a challenging language pair. Given that the meaning of a Chinese word can be related to its graphical representation, this work aims to enhance neural machine translation by using as input a combination of: words or characters and their corresponding bitmap fonts. The fact of performing the interpretation of every word or character as a bitmap font generates more informed vectorial representations. Best results are obtained when using words plus their bitmap fonts obtaining an improvement (over a competitive neural MT baseline system) of almost six BLEU, five METEOR points and ranked coherently better in the human evaluation.Peer ReviewedPostprint (published version

Chinese-Catalan: A neural machine translation approach based on pivoting and attention mechanisms

This article innovatively addresses machine translation from Chinese to Catalan using neural pivot strategies trained without any direct parallel data. The Catalan language is very similar to Spanish from a linguistic point of view, which motivates the use of Spanish as pivot language. Regarding neural architecture, we are using the latest state-of-the-art, which is the Transformer model, only based on attention mechanisms. Additionally, this work provides new resources to the community, which consists of a human-developed gold standard of 4,000 sentences between Catalan and Chinese and all the others United Nations official languages (Arabic, English, French, Russian, and Spanish). Results show that the standard pseudo-corpus or synthetic pivot approach performs better than cascade.Peer ReviewedPostprint (author's final draft

Chinese–Spanish neural machine translation enhanced with character and word bitmap fonts

Recently, machine translation systems based on neural networks have reached state-of-the-art results for some pairs of languages (e.g., German–English). In this paper, we are investigating the performance of neural machine translation in Chinese–Spanish, which is a challenging language pair. Given that the meaning of a Chinese word can be related to its graphical representation, this work aims to enhance neural machine translation by using as input a combination of: words or characters and their corresponding bitmap fonts. The fact of performing the interpretation of every word or character as a bitmap font generates more informed vectorial representations. Best results are obtained when using words plus their bitmap fonts obtaining an improvement (over a competitive neural MT baseline system) of almost six BLEU, five METEOR points and ranked coherently better in the human evaluation.Peer Reviewe

Producció científica de l'ETSEIB a Futur. Articles publicats per investigadors de l'ETSEIB l'any 2017

Postprint (author's final draft

La traducción automática en internet : Google Traductor y Baidu Translate

Aquest treball pretén analitzar si el resultat dels traductors automàtics Google Traductor i Baidu Translate en la combinació xinès-espanyol pot ajudar als estudiants de traducció amb xinès com a llengua C a tenir accés a bibliografia escrita en xinès per elaborar treballs acadèmics. Aquesta investigació consta de dues parts: d'una banda, el marc teòric en el qual s'explica en què consisteix la traducció automàtica, la posedició i quina és la situació actual de la traducció automàtica en la combinació xinès-espanyol; d'una altra, a la part pràctica compararem les traduccions de sis textos de temàtiques diferents realitzades per aquests dos traductors automàtics per veure quin és millor. A més a més, passarem un qüestionari a estudiants de traducció de xinès per conèixer la seva experiència i la seva opinió sobre la traducció automàtica del xinès a l'espanyol.Este trabajo pretende analizar si el resultado de los traductores automáticos Google Traductor y Baidu Translate en el par de lenguas chino-español puede ayudar a los estudiantes de traducción con chino como lengua C a tener acceso a bibliografía escrita en chino para elaborar trabajos académicos. Esta investigación consta de dos partes: por un lado, el marco teórico en el cual se explica en qué consiste la traducción automática, la posedición y cuál es la situación actual de la traducción automática en la combinación chino-español; por otro lado, en la parte práctica compararemos las traducciones de seis textos de temática diversa realizadas por estos dos traductores automáticos para ver cuál es mejor. Asimismo, pasaremos un cuestionario a varios estudiantes de traducción de chino para conocer su experiencia y su opinión sobre la traducción automática del chino al español.The purpose of this Bachelor's Degree Final Project is to analyse whether Google Translate and Baidu Translate automatic translators can help Chinese-Spanish translation students to clearly understand Chinese-written bibliography for academic work. This project is divided in two parts: the theoretical part, where machine translation and post-editing are defined and explained, and the current situation of Chinese-Spanish machine translation; in the practical part, we will compare the translations of six texts of different topics made by these two machine translation engines to know which one can do it better. Moreover, we will launch a questionnaire to know the experiences and opinions of Chinese translation students about Chinese-Spanish machine translation