A New Broad NLP Training from Speech to Knowledge (2021)

Abstract: In 2018, the Master Sc. in NLP opened at IDMC - Institut des Sciences du Digital, du Management et de la Cognition, Université de Lorraine - Nancy, France. Far from being a creation ex-nihilo, it is the product of a history and many reflections on the field and its teaching. This article proposes epistemological and critical elements on the opening and maintainance of this so far new master’s program in NLP.

## introduction this article discusses the epistemological background of the creation of the master of science program in natural language processing (nlp) at the university of lorraine in 2018. it puts forward a critical analysis of the environment, of the methodology chosen to produce this program, and it highlights the salient elements for the teaching of nlp. currently, the master's degree is taught at the idmc of the university de lorraine. it is accessible to students trained within the undergraduate program of the institute or to students that successfully apply to the program. a jury from the pedagogical team evaluates the adequacy of the candidates' profile with the requirements and expectations of the training. for the detailed description of the master's degree in nlp, please visit our dedicated website 3 . we propose a singular training at the french level, and probably at the international level. it is a master's degree that gives the tools and methods to carry out language data processing. if nlp is at the heart of the training, we have opened up to speech and knowledge processing. the objective is to train tomorrow's professionals in both the economic and academic fields for language data processing. in this article we present the master's degree in nlp at the idmc. we start by reviewing the historical background that is important to the current nlp master's program, before presenting the approach explaining the constitution of the program. we will then return to the program itself and discuss some structural aspects. finally, we put forward some elements of analysis. ## history the department of mathematics and computer science at the university of nancy 2 pursued a policy of opening up both of these disciplines to human and social sciences. at the beginning of the 2000s, the department proposed a training program based on these aspects by integrating economics and business management. following this interdisciplinary view, the pedagogical team created a bachelor's degree program in cognitive sciences. several thematic openings were made, in particular, towards psychology, biology, linguistics and neurosciences. the dynamics was successful and paved the way to the opening of a complete master's program in cognitive sciences (two years). the core of the training has clearly been cognitive sciences. ## definition of the nlp program the first question is to decide to whom the program is intended. to do this we went back to the ambition we wanted to give to the program. once the objective was clarified, we were able to work on defining the content of the program. ## analysis of student profiles after having presented the structure, the organization and the stakes of the training, we propose to come back on quantitative elements concerning the before the definition of the program, we had made a study on the 2008-2017 classes. we noted that 36% of the students were french, 45% from another european country and 19% from a non-european country, which is proof of a good diversity of origin. of those who continued their studies after the course, 40% joined a company, 33% were doing a thesis and 27% had an academic post. another interesting element that appears in this table, put foward in figure 1b , is the increase in the number of candidates, with 117 candidates for the m1 year in 2020-21. it should be noted that this number of applicants does not include students trained within the idmc or erasmus mundus lct students who are selected through another process. for m2 students, only a few students are selected, the majority coming from the first year of training. our experience leads us to limit even more the number of students entering the second year directly, because on the one hand these students have gaps that they are unable to fill, and on the other hand they have difficulties integrating the class. these elements must of course be put into perspective because the effects of the health crisis must also be taken into account. finally, the other axis of analysis proposed is to look at the nationalities of the students. it can be seen that the average number of french students has decreased significantly, from 44% to 34.5%. this decrease did not affect the rate of oversea students, keeping their number slightly above 50. finally, an important element is to analyze the profiles at entry with the success at the end of the master's degree. the first element is that the students who follow the two years of training have better results and rankings. this supports the idea that the training has singular characteristics that are difficult to catch up on. this is understandable because it is necessary to master concepts in computer science and linguistics, and moreover it is necessary to master the tools and methods of ai, which are specific and rather abstract. one should not believe that a profile at the entrance would be privileged in this type of training. the ringleader or the first ones of the promotions do not have a priori determined profiles. they may come from traditional computer science or linguistics. what seems to make the difference is, in addition to their aptitude at entry, their investment in the training throughout the two years. this reassures us that the aim is to bring together the profiles, while respecting their original specificities. ## conclusion and perspectives we highlighted the process of creating the master's degree in nlp at the idmc. this training is unique in that it delivers a french diploma in nlp. students who enter the program have a background either in computer science or in linguistics. the training aims to give them strong skills to train future professionals in language data processing. we have integrated collaborations with several components in our environment (erasmus mundus lct, emlex, ecole des mines, etc.). the training is attractive and has good results. students trained in this way are currently making choices between different possible careers, rather than being affected by the economic and sanitary situation due to the health crisis, that impacted negatively the job market. over the different years observed, we noticed that the number of internship proposals on the one hand and the number of job offers on the other hand, are constantly increasing. we see the search for profiles explicitly in nlp. moreover, our opening towards more applied profiles has not been at the expense of the relationship with the academic world. out of the first class that followed the 2 years of the training, 7 are pursuing a thesis which is very positive. these two dynamics reinforce our commitment to the development of the program. since the beginning of the program, we have asked for oral and written evaluations from the students on both the teaching and the organization of the training. this feedback has allowed us to improve the content while remaining within the same general framework. the integration of the students at the end of the training confirms us in the belief of the interest of the training that we have. the accreditation we have obtained is coming to an end and we must now prepare a proposal for a general evolution for 2023. the master is now considered mature and can benefit from more autonomy. for the future, we want to consolidate the training by slightly increasing the flow of students until we reach 40 students per year, especially with students from the european area. in addition, we are working on developing opportunities for research, which would allow us to offer training courses of very good quality towards phd.