Muse AI

Our goals

to increase the efficiency of
fact-checking operations.

Our goals

to scale up fact-checking tasks associated with
monitoring the web and social networks.

Our goals

to detect fact-checkable claims, as well as repetitions and spreading,
even with certain variations, of a claim.

Scope

The scope of the MuseAI project encompasses the development of a comprehensive multilingual claim detection and matching solution tailored for fact-checkers and journalists. This solution aims to address the increasing challenges associated with monitoring the web and social networks to identify fact-checkable claims, assess their check-worthiness, and detect repetitions or variations of the same claim across different languages and content sources..

Key components

Multilingual Claim Detection

The MuseAI solution will use advanced natural language processing (NLP) techniques to identify factual claims within textual content across multiple languages.

Multilingual Claim Matching

Once a claim has been identified, it must be assessed and generate an output that establishes whether it is a true or false fact (or that there is insufficient evidence to make it so).

Modality Support

The MuseAI solution will support multiple information modalities, including text, audio, and video, by incorporating automated transcription capabilities using deep learning models.

User-Friendly Interfaces

An intuitive and user-friendly interface will be developed to provide fact-checkers and journalists with seamless access to MuseAI’s functionalities.’