Over the past two decades, a team of researchers have worked\ntirelessly to continuously update and improve UM-CAT in order to meet the needs\nof the translation industry.<\/p>
Putting the Users\nFirst<\/b><\/p>
Ao Chi Hong, a research assistant in the NLP2CT,is one of\nthe core members of the team behind UM-CAT. The neural-based machine\ntranslation system, in which he was involved, won the top three awards at the\n13th China Workshop on Machine Translation. The award-winning system is one of the\ncore technologies used in developing UM-CAT. Currently, Ao is responsible for\nsystem setup and management of UM-CAT as well as ensuring good user experience.<\/p>
Ao joined the NLP2CT as a research assistant after completing\nhis bachelor\u2019s and master\u2019s degrees in computer sciences at UM. He has been\nworking in the lab for nearly eight years. He says, \u2018After working on the\nsystem for so many years, I am most happy to see its launch into the market. We\nput great emphasis on the quality of Chinese-Portuguese translation and aim for\na high degree of accuracy, especially with terms commonly used in Macao and Portuguese-speaking\ncountries. We also make sure that it is easy to use. So it is a valuable\nproduct for our target markets. It can even create a tailor-made management\nmode for a translation company to streamline the work flow and improve the\nquality of translation. These functions are lacking in many other translation\nplatforms currently available on the market.\u2019<\/p>
Improving UM-CAT\u2019s\nMachine Learning Algorithms<\/b><\/p>
Liu Xuebo, a PhD student of computer sciences in FST, is also\ninvolved in the development of UM-CAT. He is mainly responsible for improving\nthe translation quality of UM-CAT by improving its machine learning algorithms,\nwhich is also the subject of his PhD research. He explains, \u2018Machine\ntranslation includes two steps: understanding the source text and generating a\ntranslation. My work is to study how to improve the machine\u2019s ability to\nunderstand the text. Only by ensuring a high degree of accuracy will the system\nbecome a truly useful tool for the translators. And only then will they be\nhappy to use it.\u2019<\/p>
According to Dr Liu, like the majority of machine translation\nsystems in the world, UM-CAT is based on the architecture developed by the\nUniversity of Montreal in 2015. However, in 2017, Google launched a new\narchitecture, which greatly improved the quality of translation. So UM-CAT must\nbe updated to keep pace with the changing technology. Liu says, \u2018In terms of\nimproving the algorithms, only by using the latest architecture and method can\nwe ensure that the quality of the translation meets translators\u2019 requirements\nfor accuracy and readability.\u2019 In the same year, the team from the NLP2CT, led by\nProf Wong, visited Tsinghua University. As a member of the team, Liu studied\nthe latest architecture developed by Google with researchers from\nTsinghua. \u2018The biggest gain for me was that we thoroughly studied and mastered the\narchitecture,\u2019 he says.<\/p>
In November 2018, the team returned to Macao and began to\ngradually integrate the latest technologies in UM-CAT to improve the system\u2019s\nability for deep learning. Dr Liu explains: \u2018In the past, training machine\ntranslation systems relied heavily on parallel corpora. We are talking about\nmillions of Chinese texts and corresponding Portuguese translations. But now,\nwe constantly update the parameters of each neuron in the neural network. In other\nwords, each time we develop a better neural network, the quality of the\ntranslation will greatly improve as a consequence, either by reducing the occurrence\nof overlooked words, or by improving the readability of the translation.\u2019 The\nteam in theNLP2CT and their counterparts from Tsinghua University have\nsubmitted two jointly authored papers to international journals. A patent is\nalso pending for approval.<\/p>
The Market Potential\nof Machine Translation Systems<\/b><\/p>
The current version of UM-CAT was launched in December 2018,\nand the team is already working to develop a new generation of the system (G4).\nUM alumni who have been involved in the development of the system are shining\nin different professions, some in tech giants like Alibaba, Baidu, and Tencent,\nwhile others CEOs of their own businesses, contributing to the development of\nMacao and the Greater Bay Area. These alumni all feel excited to see the fruit\nof their labour being finally put to use.<\/p>
UM alumnus Tian Liang worked in the NLP2CTas a research\nassistant for one year after graduating from the master\u2019s degree programme in\ncomputer sciences in 2012. He was involved in the development of various\nmachine translation systems. In the process, he learned the huge potential in\nthe application of artificial intelligence. In 2013, he left the lab and\nregistered a science and technology company in the mainland that is focused on\ndeveloping AI voice and image technologies. He thinks that as a product made in\nMacao, UM-CAT has local characteristics and advantages. More importantly, it\ngives priority to the growing demand in Portuguese-speaking countries for\ntranslation services in Portuguese, English, Cantonese, and Mandarin. In recent\nyears, Tian started to concentrate on the Macao market. \u2018This is a time when\nmachine translation technology is developing rapidly, I hope to launch the\nrelated technologies and products in Macao and Portuguese-speaking countries.\nAlso, UM is my alma mater, I hope to launch UM-CAT on the mainland market\nthrough collaboration with the university and companies.\u2019<\/p>
A Breeding Ground for\nTech Talent<\/b><\/p>
UM alumnus Zeng Xiaodong, who graduated from the master\u2019s\ndegree programme in e-commerce technology in 2012, was involved in some\ninterdisciplinary projects in the NLP2CT while still studying at UM. In 2018,\nZeng entered the 35Innovators Under 35 China list released by MIT Technology\nReview. Former honorees on this list include Google co-founders Larry Page and\nSergey Brin, and Facebook founder Mark Zuckerberg.<\/p>
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Zeng says, \u2018I\u2019m very excited to see the project in which I\nwas involved finally being put into use. UM-CAT removes language barriers in\ncommunication.\u2019 Zeng notes that the innovative technologies he acquired in the\nNLP2CT and his experience as an exchange student in Portugal provided a\npowerful boost to his self-confidence when he later decided to start his own\nbusiness after graduation. He learned from these experiences how important it\nis to honour one\u2019s passion and pursue a career following that passion.\nCurrently, Zeng is working in Ant Financial\u2019s technology laboratory, where he\ndevotes himself to exploring new technologies based on the Internet of Things\nthat can transform the retail industry. He founded Tao Cafe, the first cashier-less\nshop in China, which enables customers to leave the shop with their items in\nhand without needing to head to a register, landing him on the MIT Technology\nReview\u2019s list. Zeng is grateful to Prof Wong Fai and Dr Chao Sam from FST for\ntheir guidance. \u2018Studying at UM gave me the opportunity to meet people from\ndifferent countries and regions. Such an open environment helps cultivate an\nopen mind. In terms of educational resources accessible to every student, UM is\narguably one of the best in China,\u2019 he says.<\/p>