Integration of Machine Translation and Translation Memory: Post-Editing Efforts (2021)

Abstract: The development of Translation Technologies, like Translation Memory and Machine Translation, has completely changed the translation industry and translator’s workflow in the last decades. Nevertheless, TM and MT have been developed separately until very recently. This ongoing project will study the external integration of TM and MT, examining if the productivity and post-editing efforts of translators are higher or lower than using only TM. To this end, we will conduct an experiment where Translation students and professional translators will be asked to translate two short texts; then we will check the post-editing efforts (temporal, technical and cognitive efforts) and the quality of the translated texts.

## introduction the way translators work has changed considerably in the last decades: with a world that is more globalised each day, the creation of texts has increased, and this has also affected and transformed the translation industry. the development of translation memory (tm) tools and machine translation (mt) systems is the result of these changes. translation memory and machine translation as applications have been used for many years by academics and professional translators, but they have been developed and studied in isolation @xcite . nonetheless, recent research suggests there is an increase in the interest of integrating these two applications. the integration of tm and mt creates new questions for all the parties involved in the translation process (translators, language service providers, clients) and academia. will the integration save time? therefore, will it also save money? will the quality of the texts be as good as a translation from scratch? even if the answer to these questions turns out to be positive (e.g., the time will be reduced and the quality maintained), another question remains: will the cognitive efforts of translators decrease? with the integration of tm and mt, more options (or segments) are presented to the translator and the translator's cognitive efforts may vary as the translation process would have one more step (explained in five simple steps): the aim of this work-in-progress paper is to compare the different types of postediting efforts (temporal, technical and cognitive) of translating with only tm or mt and translating with the combination of tm and mt. that is, calculating if the time it takes to finish a translation task is higher or lower using both technologies, checking if the technical efforts (studying the keystrokes and edits) are the same, lower, or higher; and examining if the cognitive efforts are also higher or lower using tm and mt. our initial hypothesis is that the three efforts will decrease with the combination of tm and mt, however, while there are studies about the differences between translating with tm and mt @xcite , empirical research about translating with a computer-assisted translation (cat) tool that integrates tm and mt is still limited. therefore, this ongoing project will try to answer the following research questions: rq1: will the translator save time using a system that integrates tm and mt? rq2: will the translator invest less cognitive efforts when using tm and mt? rq3: will the quality of the translation not be deteriorated when using tm systems with integrated mt? ## conclusion to sum up, we will carry out an experiment to check whether the external integration of tm and mt, where translators are able to see segments proposed by both technologies, is beneficial for translators. to do that, we will conduct a translation task, and we will assess if the temporal, technical and cognitive efforts increase or decrease. we will also check the quality of the translations, and we will collect qualitative data about the opinion of the participants with two questionnaires.