David Martins de Matos
David Martins de Matos has 5 papers in our library, in 2015–2020, most of them on Speech act theory, Dialogue systems, English; often with Eugenio Ribeiro; Ricardo Ribeiro;, Eugenio Ribeiro, Ricardo Ribeiro.
OpenAlex · ORCID · Wikidata · h-index 17 · 125 works · 876 citations OpenAlex, 2026-10-14
📄 5 works in our library · 🔗 Cited 29 times in our library · ⭐ Paper Stars ranking: #5296
Affiliations
Concepts, shelves and topics
📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 5 worksArts and Humanities · 5 worksComputer Science · 5 worksLanguage and Linguistics · 5 works
🧭 Topics 4Research subjects and languages the work is about.Dialogue systems · 5 worksSpeech act theory · 5 worksEnglish · 2 worksTokenization & segmentation · 1 work
Works by year
2020s
2010s
Papers
- The Influence of Context on Dialogue Act Recognition (2015 · 32 citations)
The paper asks how much the surrounding dialog helps a classifier decide which dialog act a segment performs, and how far back that help extends. - Deep Dialog Act Recognition using Multiple Token, Segment, and Context Information Representations (2018 · 18 citations)
The paper tackles automatic dialog act recognition: deciding what a speaker intends with each segment of a dialog, such as a question, a statement or an agreement. - A Study on Dialog Act Recognition using Character-Level Tokenization (2018 · 5 citations)
The paper asks whether dialog act recognition, which identifies the intention behind an utterance, gains from looking below the word level. - Automatic Recognition of the General-Purpose Communicative Functions defined by the ISO 24617-2 Standard for Dialog Act Annotation (2020 · 4 citations)
The paper tackles automatic labeling of dialog segments with the general-purpose communicative functions of ISO 24617-2, the dialog act annotation standard. - Mapping the Dialog Act Annotations of the LEGO Corpus into ISO 24617-2 Communicative Functions (2020 · 4 citations)
ISO 24617-2 gives dialog act research a shared annotation scheme, but very little data follows it. The only public source is the DialogBank, with 17 English and 9 Dutch dialogs, which is too small for data-hungry neural recognizers. The authors take the LEGO corpus, 347 Let's Go bus-information calls whose original…
Co-authors here
Venues
- Journal of Artificial Intelligence Research ×2: Journal of Artificial Intelligence Research 2020, Journal of Artificial Intelligence Research 2018
- Lecture notes in computer science: Lecture notes in computer science 2018
- Language Resources and Evaluation Conference (LREC): LREC 2020
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