LinTO
Open Source, Privacy-Aware Voice Assistant
The goal of the LinTO project was to develop a conversational assistant for businesses that allows its users to control a variety of services with their voices. An extension of the collaborative platform OpenPaaS, the LinTO assistant has been designed to accompany employees throughout their daily tasks and interactions.
Research and development in the LinTO project pursued two paths. The first was to create functionalities common to personal assistants, allowing users to use their voice to read their mails, consult their agendas, open and share documents, search for information and so on. The second consisted in developing advanced options to produce high-quality transcriptions of full multi-party conversations and follow conversational exchanges in order to take notes, produce relevant real time recommendations, and automatically generate meeting minutes.
LinTO has been developed both as a device that runs on the Raspberry Pi (or other ARM smart boards) and as an open-source platform that can be deployed, adapted or maintained either directly on a company’s premises or remotely as a service (SaaS).
BPI / PIA Grands Défis du Numérique (P169201)
1 April, 2018 – 31 March, 2021
Lead: LINAGORA
People
Jean-Pierre Lorré
R&D Director
Yazid Benazzouz
Autonomic Computing
Damien Lainé
Head of R&D Engineering
Wajdi Ghezaiel
Speech & Speaker Recognition
Yoann Houpert
Full Stack Developer
Julie Hunter
Head of Language team
Kate Thompson
NLP
Zied Sellami
NLP
Guokan Shang
NLP
Sarah Zribi
Project Manager
Partners
Publications
2021
2020
LinTO Platform: A Smart Open Voice Assistant for Business Environments
The 1st International Workshop on Language Technology Platforms (IWLTP)
#Ilyes Rebai, #Kate Thompson, #Sami Benhamiche, #Zied Selami, #Damien Lainé, #Jean-Pierre Lorré
Modelling Structures for Situated Discourse
Dialogue & Discourse, vol. 11 (1): 89-121
Nicholas Asher, #Julie Hunter, #Kate Thompson
Speaker-change Aware CRF for Dialogue Act Classification
The 28th International Conference on Computational Linguistics (COLING)
#Guokan Shang, Antoine Jean-Pierre Tixier, Michalis Vazirgiannis, #Jean-Pierre Lorré
Energy-based Self-attentive Learning of Abstractive Communities for Spoken Language Understanding
The 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing (AACL-IJCNLP)
#Guokan Shang, Antoine Jean-Pierre Tixier, Michalis Vazirgiannis, #Jean-Pierre Lorré
2019
Char+CV-CTC: Combining Graphemes and Consonant/Vowel Units for CTC-Based ASR Using Multitask Learning
20th Annual Conference of the International Speech Communication Association (Interspeech)
Abdelwahab Heba, Thomas Pellegrini, #Jean-Pierre Lorré, Régine Andre-Obrecht
LinTO : Assistant vocal open-source respectueux des données personnelles pour les réunions d’entreprise
Conférence Nationale sur les Applications Pratiques de l’Intelligence Artificielle (APIA)
#Jean-Pierre Lorré, Isabelle Ferrané, Francisco Madrigal, Michalis Vazirgiannis, Christophe Bourguignat
Intégration de l’assistance vocale dans les produits IoT : cas du projet LinTO
INFormatique des ORganisations et Systèmes d’Information et de Décision (INFORSID)
#Yoann Houpert, #Sami Benhamiche, #Damien Lainé, #Yazid Benazzouz, #Jean-Pierre Lorré
Weak Supervision for Learning Discourse Structure
Conference on Empirical Methods in Natural Language Processing (EMNLP)
Sonia Badene, #Kate Thompson, #Jean-Pierre Lorré, Nicholas Asher
2018
Unsupervised Abstractive Meeting Summarization with Multi-Sentence Compression and Budgeted Submodular Maximization
The 56th Annual Meeting of the Association for Computational Linguistics (ACL)
#Guokan Shang, Wensi Ding, Zekun Zhang, Antoine J.-P. Tixier, Polykarpos Meladianos, Michalis Vazirgiannis, #Jean-Pierre Lorré
