5 papers
Don't Judge Me by My Face : An Indirect Adversarial Approach to Remove Sensitive Information From Multimodal Neural Representation in Asynchronous Job Video Interviews
Léo Hemamou, Arthur Guillon, Jean-Claude Martin +1
se of machine learning for automatic analysis of job interview videos has recently seen increased interest. Despite claims of fair output regarding sensitive information such as ge…
Beam Search with Bidirectional Strategies for Neural Response Generation
Pierre Colombo, Chouchang Yang, Giovanna Varni +1
Sequence-to-sequence neural networks have been widely used in language-based applications as they have flexible capabilities to learn various language models. However, when seeking…
Improving Multimodal fusion via Mutual Dependency Maximisation
Pierre Colombo, Emile Chapuis, Matthieu Labeau +1
Multimodal sentiment analysis is a trending area of research, and the multimodal fusion is one of its most active topic. Acknowledging humans communicate through a variety of chann…
Code-switched inspired losses for generic spoken dialog representations
Emile Chapuis, Pierre Colombo, Matthieu Labeau +1
Spoken dialog systems need to be able to handle both multiple languages and multilinguality inside a conversation (\textit{e.g} in case of code-switching). In this work, we introdu…
Automatic Text Evaluation through the Lens of Wasserstein Barycenters
Pierre Colombo, Guillaume Staerman, Chloe Clavel +1
A new metric \texttt{BaryScore} to evaluate text generation based on deep contextualized embeddings e.g., BERT, Roberta, ELMo) is introduced. This metric is motivated by a new fram…