Member Highlight: Prof. Néstor Becerra Yoma

Member Highlight: Prof. Néstor Becerra Yoma
Professor, Speech Processing and Transmission Lab
Department of Electrical Engineering, Universidad de Chile, Chile

Néstor Becerra Yoma was born in Santiago, Chile. He obtained his Ph.D. from the University of Edinburgh, UK, and his M.Sc. and B.Sc. in electrical engineering from the State University of Campinas (UNICAMP), Brazil. He is a full professor at the University of Chile. He started the Speech Processing and Transmission Laboratory, where he has investigated artificial intelligence and signal processing applied to multidisciplinary topics. He was a visiting professor at Carnegie Mellon University, USA, between 2016 and 2017. He has directed many R&D projects, in addition to being the author of almost 100 articles in international research journals and conferences and of three patents. His interests include multidisciplinary research on artificial intelligence and signal processing in various fields of application, such as human-robot-interaction, health, and seismology. Between 2020 and 2021, funded by a Chilean research program to fight the COVID-19 pandemic, he led the R&D team that developed a system to assess respiratory distress on the phone with artificial intelligence. He leads an R&D team on seismology to improve tsunami and earthquake warnings. He was a member of the Expert Committee on AI of the Ministry of Science and Technology, which proposed the first national artificial intelligence policy between 2019 and 2022. He started the IEEE Chilean Signal Processing Society Chapter in 2015.

We approached Prof. Néstor Becerra Yoma  to learn more:

Why did you choose to become a faculty in the field of signal processing?

After getting my BSc degree, I worked for a telecom company. I realized I needed some freedom to follow my own ideas and build my own technology. I decided to pursue my MSc and PhD degrees in speech recognition. I was impressed with the possibility of processing spoken language with math and programming, in other words, with digital signal processing. Being a faculty allowed me the freedom and chance to be part of the speech science and technology international community. I have met many inspiring and supportive researchers in this lavish, exciting, and welcoming community. At the University of Chile, I started the Speech Processing and Transmission Lab (LPTV, "Laboratorio de Procesamiento y Transmisión de Voz") in 2000, where I have carried out all my R&D efforts within and outside speech.

How does your work affect society?

First of all, at LPTV, I have trained tens of graduate and undergraduate students who worked on my R&D projects. Participating in R&D initiatives allows students to question, criticize, and follow their ideas. This is very important, particularly in developing countries. Signal processing gives them this opportunity because it requires talent rather than expensive equipment, significantly impacting society. Moreover, AI and deep learning are increasing this opportunity window to apply signal processing to real problems. Also,  I have shown that speech processing can lead to exciting applications in human-robot interaction, education (language learning), and health (respiratory distress estimation). I started my robotic infrastructure by buying a PR2 robot (the only one in Latin America) and three NAO robots. Moreover, enhanced signal processing with deep learning tools has allowed us to address many applied problems in speech and fields such as seismology. We are working on a system to improve the tsunami and earthquake warnings online, which is very important in countries like Chile.

What challenges have you had to face to get to where you are today?

Getting funding is always an issue. Fortunately, I have had reasonable funding opportunities in Chile to conduct applied signal processing research. Also, if you are not in the US or Europe, getting recognition for your work in the international community in some technology fields is much more difficult. Fortunately, this is changing. Finally, sometimes, I think that basic research gets more attention from funding agencies than applied research. Here, we have a task to do.

What advice would you give to scientists/engineers in signal processing?

Just after finishing my PhD attended a session in an ICASSP version called "Meet the pioneers." We had the opportunity to talk to many of the best-known researchers and authors in signal processing. One of them said to us something like "Your imagination is your limit." I would say the same.

Is there anything else that you would like to add?

Talent does not choose countries or ethnicities. To those who are in a position to do so, try to give opportunities regardless of nationality or race.