I have a BSc degree in Computer Engineering (2016) and a MSc degree in Computer Science (2017) conferred by Federal University of Pará (UFPA), Brazil. I’ve also spent one year (2014) as exchange student at the Óbuda University (OE) in Budapest, Hungary. Currently, I am a PhD student in Computer Science at UFPA, in Brazil. Some of my professional experiences include speech recognition for desktop, mobile and embedded platforms; as well as in developing alternative control interfaces for people with disabilities.
PhD student in Computer Science, 2020
Current role at Federal University of Pará
MSc in Computer Science, 2017
Federal UNiversity of Pará
BSc in Computer Engineering, 2016
Federal University of Pará
What am I (supposed to be) good at?
Experience with CMU Sphinx, Kaldi, HTK, Julius and DeepSpeech for Brazilian Portuguese
Raspberry Pi, Beaglebone Black and NTC C.H.I.P. SBCs; and the Arduino platform
Software- and hardware-based solutions for people with visual, hearing and upper-limb motor disabilities
Applications for the routing and wavelength assignment (RWA) problem in wavelength-multiplexed (WDM) optical networks
Arch, Alpine, Vim, Git, Bash, Python, C, LaTeX, MATLAB (is that enough?)
Estimating the input parameter of Klatt88 formant-based speech synthesizer with long short-term memory neural nets (LSTM).
The first attempt to create scripts and baseline acoustic models for Brazilian Portuguese using Kaldi tools.
An open-source, low cost universal remote control system that translates user’s head poses into commands to electronic devices. In addition, a proximity sensor circuit was combined to radio-frequency modules in order to act as a wireless switch.
A genetic algorithm that aims at solving the RWA problem, which consists of choosing the most suitable lightpath (i.e., a combination of a route and a wavelength channel) between a source-destination pair of nodes in all-optical networks.
This paper describes a cloud speech recognition service in Brazilian Portuguese based on Julius decoder running in server mode. The client side was built on the Android 2.2 platform.