Difference between revisions of "Jaime Ferreira"
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* Master Thesis - Incremental Learning of Probabilistic Models in High-Dimensional Space | * Master Thesis - Incremental Learning of Probabilistic Models in High-Dimensional Space | ||
* SpeDial - Machine-Aided Methods for Spoken Dialogue System Enhancement and Customization for Call-Center Applications (FP7 European Project) | * SpeDial - Machine-Aided Methods for Spoken Dialogue System Enhancement and Customization for Call-Center Applications (FP7 European Project) | ||
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2014 : | 2014 : | ||
* VOCE - Voice Coaching for Reduced Stress (FCT National Project) | * VOCE - Voice Coaching for Reduced Stress (FCT National Project) | ||
Revision as of 13:21, 30 August 2016
Jaime Rodrigues Ferreira graduated in Information Systems and Computer Engineering in 2012 from Instituto Superior Técnico (IST), Lisbon. He is currently finishing his Masters Degree in Information Systems and Computer Engineering (IST). During his education he has been associated with INESC-ID's Spoken Language Systems Lab (L²F), first as a trainee, and later as scholarship holder. From this association, he participated in some internal projects, a national and an European project.
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Publications
International Journals
2018
- Vera Cabarrão, Helena Moniz, Fernando Batista, Jaime Rodrigues Ferreira, Isabel Trancoso, Ana Isabel Mata da Silva, Cross-domain analysis of discourse markers in European Portuguese, Dialogue & Discourse, vol. 9, n. 1, pages 79-106, doi: Journal doi: 10.5087/dad, June 2018
International Conferences
2016
- Fernando Batista, Pedro dos Santos Lopes Curto, Isabel Trancoso, Alberto Abad, Jaime Rodrigues Ferreira, Eugénio Ribeiro, Helena Moniz, David Martins de Matos, Ricardo Ribeiro, SPA: Web-based Platform for easy Access to Speech Processing Modules, In LREC, European Language Resources Association (ELRA), pages 3886--3892, doi: ISBN: 978-2-9517408-9-1, Portorož, Slovenia, May 2016
2015
- Eugénio Ribeiro, Jaime Rodrigues Ferreira, Julia Olcoz, Alberto Abad, Helena Moniz, Fernando Batista, Isabel Trancoso, Combining Multiple Approaches to Predict the Degree of Nativeness, In Interspeech 2015, Dresden, Germany, September 2015
- Helena Moniz, Jaime Rodrigues Ferreira, Fernando Batista, Isabel Trancoso, Disfluency Detection Across Domains, In DISS 2015, Edinburgh, Scotlan, UK, August 2015
- Vera Cabarrão, Helena Moniz, Jaime Rodrigues Ferreira, Fernando Batista, Isabel Trancoso, Ana Isabel Mata da Silva, Sérgio dos Santos Lopes Curto, Prosodic Classification of Discourse Markers, In International Congress of Phonetic Sciences (ICPhS 2015), Glasgow, Scotland, UK, August 2015
National Journals
2016
- Vera Cabarrão, Helena Moniz, Jaime Rodrigues Ferreira, Fernando Batista, Isabel Trancoso, Ana Isabel Mata da Silva, Sérgio dos Santos Lopes Curto, Classificação prosódica de marcadores discursivos, Revista da Associação Portuguesa de Linguística, n. 2, pages 69 -- 95, July 2016
National Conferences
2015
- Mariana Juliao, Jorge Silva, Ana Aguiar, Helena Moniz, Jaime Rodrigues Ferreira, Fernando Batista, Speech Features for Discriminating Stress, In 10th Conference on Telecommunications, Conftele 2015, IT, https://www.it.pt/Publications/PaperConference/224, September 2015
Masters Theses
2015
- Jaime Rodrigues Ferreira, Incremental Learning of Probabilistic Models in High-Dimensional Space, MSc thesis, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, October 2015
Other Publications
2016
- Jaime Rodrigues Ferreira, David Martins de Matos, Ricardo Ribeiro, Fast and Extensible Online Multivariate Kernel Density Estimation, https://arxiv.org/abs/1606.02608, June 2016
Research Interests
- Computer Vision
- Machine Learning
- Big Data
- Speech Prosody
Completed Projects
2015 :
- Master Thesis - Incremental Learning of Probabilistic Models in High-Dimensional Space
- SpeDial - Machine-Aided Methods for Spoken Dialogue System Enhancement and Customization for Call-Center Applications (FP7 European Project)
2014 :
- VOCE - Voice Coaching for Reduced Stress (FCT National Project)
2011 :
- Face Recognition system via Principal Component Analysis