Search Results for author: José Lopes

Found 8 papers, 4 papers with code

Going for GOAL: A Resource for Grounded Football Commentaries

1 code implementation8 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.

Moment Retrieval Retrieval

Exploring Multi-Modal Representations for Ambiguity Detection & Coreference Resolution in the SIMMC 2.0 Challenge

2 code implementations25 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.

coreference-resolution

Domain Adaptation in Dialogue Systems using Transfer and Meta-Learning

no code implementations22 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.

Domain Adaptation Meta-Learning

The Lab vs The Crowd: An Investigation into Data Quality for Neural Dialogue Models

1 code implementation7 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.

CRWIZ: A Framework for Crowdsourcing Real-Time Wizard-of-Oz Dialogues

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.

Natural Language Interaction to Facilitate Mental Models of Remote Robots

no code implementations12 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.

The Spot the Difference corpus: a multi-modal corpus of spontaneous task oriented spoken interactions

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.

Assessing User Expertise in Spoken Dialog System Interactions

no code implementations18 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.

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