The concept of data anonymisation Broadly speaking, data anonymisation can be defined as the process of irreversibly removing identifiable (confidential or private) information of both natural and legal persons[1] from raw datasets (e.g., text databases, audio recordings, etc.) [Ref1]. But there is more about anonymisation than what meets the eye,…
Discover COMPRISE Weakly Supervised NLU, an innovative automatic data labelling and model training software for Natural Language Understanding (NLU). Today’s Deep Learning technology is hungry for data – the more, the better. But for many tasks, raw data is not enough: every sample of data needs to be labelled first,…
The Cost Factor behind Speech-to-Text Technology Voice assistants equipped with Speech-to-Text technology have seen a major boost in performance and usage, thanks to the new powerful machine learning methods based on deep neural networks. These methods follow a supervised learning approach, requiring large amounts of paired speech-text data to train…
Emmanuel Vincent (COMPRISE’s Project Coordinator) has just published an article titled “”Peut-on faire confiance aux IA ?” (the translation in English is “Can AI systems be trusted?”) in The Conversation. Read it at the following link!
COMPRISE SDK Thanks to COMPRISE SDK, developers can create multilingual, voice-enabled applications in a faster, cost-effective, and privacy-driven way. The SDK is made for Smartphone applications developed with the Ionic framework, with Angular as a foundation. It consists of: the COMPRISE Personal Server, which allows the execution of large related…
The emergence of e-commerce platforms combined with the mobile revolution has changed the way millions of users around the world discover, select and order goods. These platforms are evolving at an incredibly fast pace to become a complete environment in which end-users (i.e., customers) are able to place orders within…
Voice technologies are being used in fields as diverse as medicine and education, but also for pure leisure. This article offers an overview of how categorisation and contextualisation can be used as methods not only to identify personal information but to design private-by-design voice-based solutions that intend to neutralise personal data and information/words that…
The joint efforts of the COMPRISE consortium continue bearing results as COMPRISE SDK has been released. With COMPRISE SDK, developers can create multilingual, voice-enabled applications in a faster, cost-effective, privacy-driven way. Check our press-release about our released tool!
In a world with more than 7,000 languages, roughly half of the people speak only one language, thus creating huge barriers that restrict cross-cultural communication. Thanks to advances in Artificial Intelligence and Machine Learning, we are steadily moving towards a future where hosting a dinner party for 20 guests, each…
Not just yet another note taking app Note taking apps are very useful in many situations. They can be used as a creative backlog for the user’s job, as a to-do list for household tasks or maybe as a shopping list. There are as many options as the number of…
The Call For Papers for the Privacy Preserving Machine Learning Workshop at NeurIPS 2020 (co- organized by our partner Aurelien Bellet, from INRIA) is open now !! This one day workshop focuses on privacy preserving techniques for machine learning and disclosure in large scale data analysis, both in the distributed…
Overview Are you a developer? Thanks to the COMPRISE SDK, you can now create multilingual, voice-enabled applications in a faster, cost-effective, and privacy-driven way. The SDK is made for Smartphone applications developed with the Ionic framework, with Angular as a foundation. It consists of: The COMPRISE Client Library, which can…
