2 citations · 2 across the 3 of their papers we have counts for
6 papers
Evaluate On-the-job Learning Dialogue Systems and a Case Study for Natural Language Understanding
Mathilde Veron, Sophie Rosset, Olivier Galibert +1
On-the-job learning consists in continuously learning while being used in production, in an open environment, meaning that the system has to deal on its own with situations and ele…
LIMSI_UPV at SemEval-2020 Task 9: Recurrent Convolutional Neural Network for Code-mixed Sentiment Analysis
Somnath Banerjee, Sahar Ghannay, Sophie Rosset +2
This paper describes the participation of LIMSI UPV team in SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text. The proposed approach competed in SentiMix Hin…
A Comparison of Metric Learning Loss Functions for End-To-End Speaker Verification
Juan M. Coria, Hervé Bredin, Sahar Ghannay +1
Despite the growing popularity of metric learning approaches, very little work has attempted to perform a fair comparison of these techniques for speaker verification. We try to fi…
DiaBLa: A Corpus of Bilingual Spontaneous Written Dialogues for Machine Translation
Rachel Bawden, Sophie Rosset, Thomas Lavergne +1
We present a new English-French test set for the evaluation of Machine Translation (MT) for informal, written bilingual dialogue. The test set contains 144 spontaneous dialogues (5…
Survey on Evaluation Methods for Dialogue Systems
Jan Deriu, Alvaro Rodrigo, Arantxa Otegi +4
In this paper we survey the methods and concepts developed for the evaluation of dialogue systems. Evaluation is a crucial part during the development process. Often, dialogue syst…
Natural language understanding for task oriented dialog in the biomedical domain in a low resources context
Antoine Neuraz, Leonardo Campillos Llanos, Anita Burgun +1
In the biomedical domain, the lack of sharable datasets often limit the possibility of developing natural language processing systems, especially dialogue applications and natural…