Amanda Duarte

Position	e-mail
PhD Candidate	amanda.duarte@upc.edu

Office	Phone
C6 E201	+34 934054282.

Biography

In 2015, she graduated in Systems Analysis at Instituto Federal Sul-rio-grandense Câmpus Pelotas (IFSul) in Brazil spending one year at Northern Virginia Community College (NVCC) in the United States as part of an exchange program. She obtained her Master's degree in Computer Engineering from Universidade Federal do Rio Grande (Furg) under the supervision of Prof. Silvia Botelho and Prof. Paulo Drews working with the Automation and Intelligent Robotics (NAUTEC) group.

During the summer of 2017, she was a visiting student at .

Over the course of her PhD, she interned at the Barcelona Supercomputing Center, Johns Hopkins University and Carnegie Mellon University in 2017, 2018 and 2019, respectively.

Her current research interests lie in the area of Computer Vision and Machine Learning applied to accessibility.

For more information, visit her personal webpage.

News

[05/2020] Grounded Sequence to Sequence Transduction accepted at IEEE Journal of Selected Topics in Signal Processing
[10/2019] Presenting my reserach proposal titled Cross-modal Neural Sign Language Translation at ACM Multimedia 2019 at the Doctoral Symposium
[Spring 2019] Visiting Student at Carnegie Mellon University
[05/2019] Our paper Wav2Pix: Speech-conditioned Face Generation using Generative Adversarial Networks was accepted at ICASSP 2019
[10/2018] Received a Marie Skłodowska-Curie fellowship through the INPhINIT - ”La Caixa” Doctoral fellowship
[Summer 2018] Participating on the Frederick Jelinek Memorial Summer Workshop 2018
[12/2017]: Presenting our work Temporal-aware Cross-modal Embeddings for Video and Audio Retrieval at Woman in Machine Learning (WiML) Workshop 2017.
[09/2017]: Awarded with a Caffe2 Research Grant by Facebook.
[09/2017]: Teaching assistant of the first NVIDIA Deep Learning Institute Workshop as part of the University Ambassador Program.

2020
A. Duarte, Palaskar, S., Ghadiyaram, D., DeHaan, K., Metze, F., Torres, J., and Giró-i-Nieto, X., “How2Sign: A Large-scale Multimodal Dataset for Continuous American Sign Language”, in ECCV 2020 Workshop on Sign Language Recognition, Translation and Production (SLRTP), 2020. Google Scholar BibTex (744.94 KB)
L. Ventura, Duarte, A., and Giró-i-Nieto, X., “Can Everybody Sign Now? Exploring Sign Language Video Generation from 2D Poses”, in ECCV 2020 Workshop on Sign Language recognition, Production and Translation (SLRTP), 2020. Google Scholar BibTex (3.85 MB)

2019
A. Duarte, Roldán, F., Tubau, M., Escur, J., Pascual-deLaPuente, S., Salvador, A., Mohedano, E., McGuinness, K., Torres, J., and Giró-i-Nieto, X., “Wav2Pix: Speech-conditioned Face Generation using Generative Adversarial Networks”, in ICASSP, Brighton, UK, 2019. DOI Google Scholar BibTex (4.42 MB)
A. Duarte, “Cross-modal Neural Sign Language Translation”, in Proceedings of the 27th ACM International Conference on Multimedia - Doctoral Symposium, Nice, France, 2019. DOI Google Scholar BibTex (392.69 KB)

2018
D. Surís, Duarte, A., Salvador, A., Torres, J., and Giró-i-Nieto, X., “Cross-modal Embeddings for Video and Audio Retrieval”, in ECCV 2018 Women in Computer Vision Workshop, Munich, Germany, 2018. DOI Google Scholar BibTex (1.07 MB)

2019
M. Tubau, “Wav2Pix: Enhancement and Evaluation of a Speech-conditioned Image Generator”. 2019. Google Scholar BibTex	Ms Thesis

2018
S. Roca, “Block-based Speech-to-Speech Translation”. 2018. Google Scholar BibTex (505.01 KB)	Ms Thesis

	Cross-modal Deep Learning between Vision, Language, Audio and Speech	European	Oct 2018	Sep 2020
	Speech2Signs: Spoken to Sign Language Translation using Neural Networks	Other	Nov 2017	Nov 2018

Acronym	Title	Level	College
DLCV	Deep Learning for Computer Vision	Master in Telecommunications Engineering (MET)	ETSETB Telecom BCN