LINAGORA Labs, R&D team

Bringing you our experience, our relationships and the full range of our services for your projects around open source software.

labs.linagora.com
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LINAGORA Labs in Toulouse and Paris

The Research and Development (R&D) teams, gathered within the "LINAGORA Labs" entity include engineers, researchers, and PhD students who are experts in artificial intelligence, machine learning and DevOps.

Located in Toulouse and Paris, our researchers work to create innovation. The goal is to give back our work to open-source communities and to enable the improvement and design of products with high usage value.

The team is actively involved in leading French and European research projects and focuses on topics such as artificial intelligence, speech recognition, cloud platforms and natural language processing.

Crédit photo: Jacquym, CC BY-SA 4.0, via Wikimedia Commons

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Linagora's commitment

We study the scientific locks that allow us to propose ethical technological innovations that are independent of GAFAM (Google, Apple, Facebook, Amazon and Microsoft) and BATX (Baidu, Alibaba, Tencent and Xiaomi).

They are part of the creation of a 3rd digital way based on the philosophy stemming from free software. Moreover, we are convinced that Europe can build a new, more inclusive and sustainable IT world.

Artificial Intelligence (AI) ethics

LINAGORA has recently undertaken significant R&D efforts in the field
of ethical Artificial Intelligence (AI). Approaches stemming from AI and especially Machine Learning are indeed promising in relation to the subjects we wish to position ourselves on. The ethical character is linked to the respect of personal data and the transparency of the algorithms
permitted by the open-source model.

Collaborative Research Projects

LINAGORA Labs participates in collaborative research projects to study and remove scientific
and technical barriers associated with its software product offering. These projects funded
by the European Commission and the French State involve prestigious international research laboratories
and innovative companies.

Collaborations

LINAGORA Labs collaborates intensively with academic and industrial research laboratories. This collaboration takes various forms:

Publications

  • LinTO : Assistant vocal open-source respectueux des données personnelles pour les réunions d’entreprise

    Jean-Pierre Lorré, Isabelle Ferrané, Francisco Madrigal, Michalis Vazirgiannis, Christophe Bourguignat (2019). LinTO : Assistant vocal open-source respectueux des données personnelles pour les réunions d’entreprise. Dans APIA 2019 : Conférence Nationale sur les Applications Pratiques de l'Intelligence Artificielle. Association Française pour l’Intelligence Artificielle, pp 63–66.

  • LinTO Platform: A Smart Open Voice Assistant for Business Environments

    Ilyes Rebai, Kate Thompson, Sami Benhamiche, Zied Sellami, Damien Laine, Jean-Pierre Lorré (2019). LinTO Platform: A Smart Open Voice Assistant for Business Environments. Dans The 1st International Workshop on Language Technology Platforms (IWLTP 2020).

  • Unsupervised Abstractive Meeting Summarization with Multi-Sentence Compression and Budgeted Submodular Maximization

    Guokan Shang, Wensi Ding, Zekun Zhang, Antoine Tixier, Polykarpos Meladianos, Michalis Vazirgiannis, Jean-Pierre Lorré (2018). Unsupervised Abstractive Meeting Summarization with Multi-Sentence Compression and Budgeted Submodular Maximization. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, pp. 664—674

  • Data Programming for Learning Discourse Structure

    Sonia Badene, Kate Thompson, Jean-Pierre Lorré, Nicholas Asher (2019). Data Programming for Learning Discourse Structure. Dans Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, pp. 640–645.

  • Weak Supervision for Learning Discourse Structure

    Sonia Badene, Kate Thompson, Jean-Pierre Lorré, Nicholas Asher (2019). Weak Supervision for Learning Discourse Structure. Dans Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, pp. 2296–
    2305.

More on our dedicated R&D website

labs.linagora.com

Contact-Us

You can help us in many ways!

Email: info@linagora.com

Give us a call or drop by anytime, we endeavour to answer all enquiries within 24 hours on business days.

+33 (0)1 46 96 63 63

We are open from 9am — 6pm week days.