The Learning Curve, Part 5: Overcoming Multicultural and Multilingual Differences

Samsung Research in Brazil is part of a series about the people and innovations behind the democratization of mobile AI

As Samsung continues to pioneer premium mobile AI experiences, we visit Samsung Research centers around the world to learn how Galaxy AI is enabling more users to maximize their potential. Galaxy AI now supports 16 languages, so more people can expand their language capabilities, even when offline, thanks to on-device translation in features such as Live Translate, Interpreter, Note Assist and Browsing Assist. But what does AI language development involve? Last time, we visited China to learn about the importance of partnering with other leaders in AI. This time, we’re in Brazil to explore how teams work across cultures and borders to bring Galaxy AI to more people.

A diverse country with more than 203 million people embodying a wide range of cultures and traditions, Brazil uses Brazilian Portuguese as its official language. Meanwhile, 22 neighboring countries use Latin American Spanish.

Although Brazilian Portuguese and Latin American Spanish are widely spoken, intricate variations in both languages presented various challenges when teaching Galaxy AI to discern and distinguish regional differences. That’s why Samsung R&D Institute Brazil (SRBR) collaborated with Samsung experts from Mexico — as well as third-party partners such as the science and technology institutes SiDi and Sidia — to assemble a multidisciplinary and highly skilled team that could tackle the task.

Lower Barriers, Higher Understanding

The team used thousands of sources and a combination of machine learning and language processing tools to improve the AI model’s recognition of speech, written texts and regional variations. But local jargon and names of famous figures — including sports teams, celebrities and bands — vary widely between regions. Also, the same meaning can be expressed in many different words. While language models need localized data to gain a comprehensive understanding of the different languages to be translated, such variations inevitably present obstacles.

For example, swimming pool is “alberca” in Mexico — but it is “pileta” in Argentina, Paraguay and Uruguay. Meanwhile, in Colombia, Bolivia and Venezuela, swimming pool is “piscina”, which is also used in Brazil but with a slight tonal difference. And while Colombians might say “chévere” to refer to something cool, Mexicans instead say “padre.”

These differences represent huge challenges for AI language understanding and learning, but the team overcame them by building larger language models, refining processing tools — and collaborating across borders and time zones.

“We had to consider local slang and different ways of speaking before adapting and testing the model accordingly, which required close collaboration between the SRBR quality assurance (QA) team and development teams,” says Mateus Pedroso, Senior Manager and Head of Software Quality Lab at SRBR. “Since SRBR is located three hours ahead of the QA team in Mexico and 12 hours behind the management team in Korea, we had to create new communication channels and processes to align results and share progress. This multicultural collaboration generated a fiesta of ideas and solutions for Galaxy AI.”

Communicating Success

Samsung’s philosophy of open collaboration came to life during this regional project as it was an iterative process that leveraged evolving technology on a global scale. To overcome linguistic and cultural barriers, the SRBR team needed to collect and manage massive amounts of data — continually refining and improving upon audio and text sources.

The teams carved out key areas of responsibility to ensure everyone could benefit from the collective skill sets across the company’s Latin American offices. The SRBR development team served as the intermediate stakeholder of the project, receiving directions from Samsung’s headquarters and developing new updates to improve the AI model while carrying out tests for numerous use cases.

“The testing phase required extensive communication and collaboration with QA teams to optimize the user experience, and each adjustment needed further testing and review,” says Leandro Flores de Moura, Software Development Manager at SiDi. “The success of Galaxy AI’s language capabilities is built on communication and collaboration as much as it is on technical expertise” adds Nathan Castro, QA Test Developer at SiDi.

A Roadmap for Culture

What makes Galaxy AI particularly interesting for everyone involved is the fact that this wasn’t merely a language project. To them, language is a cultural guide that provides valuable insight into people’s heritage and identity.

“For SiDi’s QA team, this was an endeavor that will change the world by enabling cultures to come together and overcome the difficulty of communicating in different languages,” adds Estefanía Castro Suárez, Test Developer at SiDi. “Knowing we were part of this fills us with pride and motivation.”

“The way the SRBR team collaborated exemplifies what Galaxy AI sets out to achieve — making the world a smaller place through communicating, sharing and interacting with people, even those who speak different languages,” concludes Pedroso. “This capability will only grow as more languages come on board with Galaxy AI.”