Master's degree in Automatic Language Processing (ALP)

The aim of the Master's program is to train students in the methods and tools of automatic language processing, the "language" side of Artificial Intelligence, particularly for languages in the Inalco domain. NLP (for Natural Language Processing in the industrial world) can be used for research in the humanities and social sciences, for example, to analyze and describe phenomena that would otherwise be impossible to observe (digital humanities). It can also be used to develop programs that automate large-scale processing of large volumes of data: automatic translation, text generation (summarization, synthesis, question-answer systems), speech recognition, information extraction, text mining, etc.

The Master's degree in Automatic Language Processing is co-accredited by Sorbonne Nouvelle Université, Paris Nanterre and Inalco. It offers 3rd cycle training in linguistic engineering with, in M1, a common core for students from the three partner universities including, among other things, courses in linguistics, corpus constitution, programming, algorithms, engineering, etc. In the second year (M2), there are 3 possible courses: either Research and Development (for academic careers in NLP), or Multilingual Engineering, for professions linked to AI and language applications (NLP scientist, data scientist), or Translation Technologies and Multilingual Data Processing, for new translation professions (machine translation, post-editing, etc.).)

In M1, the core courses are "Gestion Informatique du Multilinguisme", "Programmation et Projet Encadré", "Corpus Parallèles et Comparables", "Informatique et Phonétique", "Statistiques Textuelles", "Document Structuré", "Syntax", "Bases de Données pour Linguistes". These courses take place on one of the 3 sites of the partner establishments. A dedicated website,, gives more information on this common core.

In M2, whatever the course, all courses take place at Inalco. Students must complete a 6-month internship. They must also write and defend a research dissertation, the subject of which is developed during the second semester. This dissertation accounts for 25% of the final assessment. It provides access to doctoral training provided by the Texts Computing Multilingualism Research Team (ERTIM) at Inalco or elsewhere.

Specialities of the TAL master's degree

The TAL master's degree is organized into 3 tracks:
- Research and Development (co-accredited with Sorbonne Nouvelle Université and Paris Nanterre)
- Multilingual Engineering (professional track)
- Translation Technologies and Multilingual Data Processing (professional track)

Target audience

The master's training approach is based on students' language skills. It is aimed at:
- students combining significant computer science knowledge and wishing to enhance language skills with a view to working in the fields of linguistic engineering and AI,
- language or linguistics students who do not necessarily have technical skills but wish to acquire them in order to promote their integration into the world of work, particularly in the professions of translation, NLP, with a multilingual specificity.

Career opportunities

There are a wide range of careers in the language industries. Opportunities are available in specialized startups (Metyis, Aday, Proxem, Labsense, Cerence, Viasema,, Linagora, Clustaar, etc.), or with dedicated R&D departments of major corporations (Orange, BNP Paribas, Dassault Systèmes, SNCF, European Space Agency, Systran, Acolad). These same companies and many others (small and medium-sized, national and international organizations), for the services they offer or for their own needs, can also call on specialists in the fields of digital information production, organization and management. Careers are mainly at engineering level.


Students wishing to apply for the TAL Master's degree must:

  • either hold a Licence LLCER in Automatic Language Processing from Inalco.
  • or have a sufficient level of proficiency in a language taught at Inalco and demonstrate competence in linguistics or computer science.