1 code implementation • 8 Nov 2022 • Alessandro Suglia, José Lopes, Emanuele Bastianelli, Andrea Vanzo, Shubham Agarwal, Malvina Nikandrou, Lu Yu, Ioannis Konstas, Verena Rieser
As the course of a game is unpredictable, so are commentaries, which makes them a unique resource to investigate dynamic language grounding.
2 code implementations • 25 Feb 2022 • Javier Chiyah-Garcia, Alessandro Suglia, José Lopes, Arash Eshghi, Helen Hastie
Anaphoric expressions, such as pronouns and referential descriptions, are situated with respect to the linguistic context of prior turns, as well as, the immediate visual environment.
no code implementations • 22 Feb 2021 • Rui Ribeiro, Alberto Abad, José Lopes
We evaluated our model on the MultiWOZ dataset and outperformed DiKTNet in both BLEU and Entity F1 scores when the same amount of data is available.
1 code implementation • 7 Dec 2020 • José Lopes, Francisco J. Chiyah Garcia, Helen Hastie
Challenges around collecting and processing quality data have hampered progress in data-driven dialogue models.
1 code implementation • LREC 2020 • Francisco J. Chiyah Garcia, José Lopes, Xingkun Liu, Helen Hastie
Large corpora of task-based and open-domain conversational dialogues are hugely valuable in the field of data-driven dialogue systems.
no code implementations • 12 Mar 2020 • Francisco J. Chiyah Garcia, José Lopes, Helen Hastie
Increasingly complex and autonomous robots are being deployed in real-world environments with far-reaching consequences.
no code implementations • LREC 2018 • José Lopes, Nils Hemmingsson, Oliver Åstrand
This paper describes the Spot the Difference Corpus which contains 54 interactions between pairs of subjects interacting to find differences in two very similar scenes.
no code implementations • 18 Jan 2017 • Eugénio Ribeiro, Fernando Batista, Isabel Trancoso, José Lopes, Ricardo Ribeiro, David Martins de Matos
Identifying the level of expertise of its users is important for a system since it can lead to a better interaction through adaptation techniques.