Search Results for author: David Martins de Matos

Found 38 papers, 0 papers with code

Story Generation from Visual Inputs: Techniques, Related Tasks, and Challenges

no code implementations4 Jun 2024 Daniel A. P. Oliveira, Eugénio Ribeiro, David Martins de Matos

These tasks share common challenges with visual story generation and have served as inspiration for the techniques used in the field.

Question Answering Story Generation +2

Computational analysis of the language of pain: a systematic review

no code implementations24 Apr 2024 Diogo A. P. Nunes, Joana Ferreira-Gomes, Fani Neto, David Martins de Matos

Only one study measured how physician performance on clinical tasks improved with the inclusion of the proposed algorithm.


Chronic pain patient narratives allow for the estimation of current pain intensity

no code implementations31 Oct 2022 Diogo A. P. Nunes, Joana Ferreira-Gomes, Daniela Oliveira, Carlos Vaz, Sofia Pimenta, Fani Neto, David Martins de Matos

We show that language features from patient narratives indeed convey information relevant for pain intensity estimation, and that our computational models can take advantage of that.


Transfer-learning for video classification: Video Swin Transformer on multiple domains

no code implementations18 Oct 2022 Daniel Oliveira, David Martins de Matos

From the results, we conclude that VST generalizes well enough to classify out-of-domain videos without retraining when the target classes are from the same type as the classes used to train the model.

Transfer Learning Video Classification

Towards Learning Through Open-Domain Dialog

no code implementations7 Feb 2022 Eugénio Ribeiro, Ricardo Ribeiro, David Martins de Matos

The development of artificial agents able to learn through dialog without domain restrictions has the potential to allow machines to learn how to perform tasks in a similar manner to humans and change how we relate to them.

Open-Domain Dialog

Chronic Pain and Language: A Topic Modelling Approach to Personal Pain Descriptions

no code implementations1 Sep 2021 Diogo A. P. Nunes, Joana Ferreira Gomes, Fani Neto, David Martins de Matos

Chronic pain is recognized as a major health problem, with impacts not only at the economic, but also at the social, and individual levels.

Management Topic Models

Mapping the Dialog Act Annotations of the LEGO Corpus into ISO 24617-2 Communicative Functions

no code implementations LREC 2020 Eug{\'e}nio Ribeiro, Ricardo Ribeiro, David Martins de Matos

Although this does not lead to a complete annotation according to the standard, the 347 dialogs provide a relevant amount of data that can be used in the development of automatic communicative function recognition approaches, which may lead to a wider adoption of the standard.

Automatic Recognition of the General-Purpose Communicative Functions defined by the ISO 24617-2 Standard for Dialog Act Annotation

no code implementations7 Mar 2020 Eugénio Ribeiro, Ricardo Ribeiro, David Martins de Matos

We explore the recognition of general-purpose communicative functions in the DialogBank, which is a reference set of dialogs annotated according to this standard.

Transfer Learning

Hierarchical Multi-Label Dialog Act Recognition on Spanish Data

no code implementations29 Jul 2019 Eugénio Ribeiro, Ricardo Ribeiro, David Martins de Matos

Concerning the single-label classification problem posed by the top level, we show that the conclusions drawn on English data also hold on Spanish data.

Multi-Label Classification

Low-dimensional Embodied Semantics for Music and Language

no code implementations20 Jun 2019 Francisco Afonso Raposo, David Martins de Matos, Ricardo Ribeiro

We further show that joint modeling of several subjects increases the semantic richness of the learned latent vector spaces.

Topic Classification

Learning Embodied Semantics via Music and Dance Semiotic Correlations

no code implementations25 Mar 2019 Francisco Afonso Raposo, David Martins de Matos, Ricardo Ribeiro

Music semantics is embodied, in the sense that meaning is biologically mediated by and grounded in the human body and brain.

Cross-Modal Retrieval Retrieval

Learning multimodal representations for sample-efficient recognition of human actions

no code implementations6 Mar 2019 Miguel Vasco, Francisco S. Melo, David Martins de Matos, Ana Paiva, Tetsunari Inamura

In this work we present \textit{motion concepts}, a novel multimodal representation of human actions in a household environment.

Deep Dialog Act Recognition using Multiple Token, Segment, and Context Information Representations

no code implementations23 Jul 2018 Eugénio Ribeiro, Ricardo Ribeiro, David Martins de Matos

Recently, most approaches to the task explored different DNN architectures to combine the representations of the words in a segment and generate a segment representation that provides cues for intention.

Word Embeddings

A Study on Dialog Act Recognition using Character-Level Tokenization

no code implementations18 May 2018 Eugénio Ribeiro, Ricardo Ribeiro, David Martins de Matos

In both cases, the experiments not only show that character-level tokenization leads to better performance than the typical word-level approaches, but also that both approaches are able to capture complementary information.

Towards Deep Modeling of Music Semantics using EEG Regularizers

no code implementations14 Dec 2017 Francisco Raposo, David Martins de Matos, Ricardo Ribeiro, Suhua Tang, Yi Yu

Modeling of music audio semantics has been previously tackled through learning of mappings from audio data to high-level tags or latent unsupervised spaces.

Cross-Modal Retrieval EEG +2

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.

An Information-theoretic Approach to Machine-oriented Music Summarization

no code implementations7 Dec 2016 Francisco Raposo, David Martins de Matos, Ricardo Ribeiro

Our results suggest that relative entropy is a good predictor of summarization performance in the context of tasks relying on a bag-of-features model.

Fast and Extensible Online Multivariate Kernel Density Estimation

no code implementations8 Jun 2016 Jaime Ferreira, David Martins de Matos, Ricardo Ribeiro

We present xokde++, a state-of-the-art online kernel density estimation approach that maintains Gaussian mixture models input data streams.

Computational Efficiency Density Estimation

Generation of Multimedia Artifacts: An Extractive Summarization-based Approach

no code implementations13 Aug 2015 Paulo Figueiredo, Marta Aparício, David Martins de Matos, Ricardo Ribeiro

We explore methods for content selection and address the issue of coherence in the context of the generation of multimedia artifacts.

Diversity Extractive Summarization

Privacy-Preserving Multi-Document Summarization

no code implementations6 Aug 2015 Luís Marujo, José Portêlo, Wang Ling, David Martins de Matos, João P. Neto, Anatole Gershman, Jaime Carbonell, Isabel Trancoso, Bhiksha Raj

State-of-the-art extractive multi-document summarization systems are usually designed without any concern about privacy issues, meaning that all documents are open to third parties.

Document Summarization Multi-Document Summarization +1

Summarization of Films and Documentaries Based on Subtitles and Scripts

no code implementations3 Jun 2015 Marta Aparício, Paulo Figueiredo, Francisco Raposo, David Martins de Matos, Ricardo Ribeiro, Luís Marujo

We assess the performance of generic text summarization algorithms applied to films and documentaries, using the well-known behavior of summarization of news articles as reference.

Text Summarization

The Influence of Context on Dialogue Act Recognition

no code implementations2 Jun 2015 Eugénio Ribeiro, Ricardo Ribeiro, David Martins de Matos

We performed experiments on the widely explored Switchboard corpus, as well as on data annotated according to the recent ISO 24617-2 standard.

Using Generic Summarization to Improve Music Information Retrieval Tasks

no code implementations23 Mar 2015 Francisco Raposo, Ricardo Ribeiro, David Martins de Matos

We evaluate the summarization process on binary and multiclass music genre classification tasks, by comparing the performance obtained using summarized datasets against the performances obtained using continuous segments (which is the traditional method used for addressing the previously mentioned time constraints) and full songs of the same original dataset.

General Classification Genre classification +4

On the Application of Generic Summarization Algorithms to Music

no code implementations18 Jun 2014 Francisco Raposo, Ricardo Ribeiro, David Martins de Matos

Several generic summarization algorithms were developed in the past and successfully applied in fields such as text and speech summarization.

General Classification

Revising the annotation of a Broadcast News corpus: a linguistic approach

no code implementations LREC 2014 Vera Cabarr{\~a}o, Helena Moniz, Fern Batista, o, Ricardo Ribeiro, Nuno Mamede, Hugo Meinedo, Isabel Trancoso, Ana Isabel Mata, David Martins de Matos

This paper presents a linguistic revision process of a speech corpus of Portuguese broadcast news focusing on metadata annotation for rich transcription, and reports on the impact of the new data on the performance for several modules.

speech-recognition Speech Recognition

Ensemble Detection of Single & Multiple Events at Sentence-Level

no code implementations24 Mar 2014 Luís Marujo, Anatole Gershman, Jaime Carbonell, João P. Neto, David Martins de Matos

Event classification at sentence level is an important Information Extraction task with applications in several NLP, IR, and personalization systems.

Classification General Classification +2

Centrality-as-Relevance: Support Sets and Similarity as Geometric Proximity

no code implementations16 Jan 2014 Ricardo Ribeiro, David Martins de Matos

In automatic summarization, centrality-as-relevance means that the most important content of an information source, or a collection of information sources, corresponds to the most central passages, considering a representation where such notion makes sense (graph, spatial, etc.).

Co-Multistage of Multiple Classifiers for Imbalanced Multiclass Learning

no code implementations23 Dec 2013 Luis Marujo, Anatole Gershman, Jaime Carbonell, David Martins de Matos, João P. Neto

In this work, we propose two stochastic architectural models (CMC and CMC-M) with two layers of classifiers applicable to datasets with one and multiple skewed classes.

Event Detection General Classification +2

Building and Exploring Semantic Equivalences Resources

no code implementations LREC 2012 Gracinda Carvalho, David Martins de Matos, Vitor Rocio

The WES base was built for the Portuguese Language, with the same format of another freely available thesaurus for the same language, the TeP base, which allows integration of equivalences both at word level and entity level.

Information Retrieval Opinion Mining +1

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