How working over continents and time zones shaped the Samsung European center for AI language development
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 India to learn how teams collaborate with students and universities to bring Galaxy AI to more people. This time, we’re in Poland to discover how European countries collaborate to accomplish their goal.
There’s a saying at the Samsung R&D Institute Poland (SRPOL): “A day at SRPOL lasts 96 hours”. It refers to the center’s global role as one of the largest and fastest-growing R&D centers in the region, often working across four different time zones. Sitting at the heart of Europe while covering many European and global markets, SRPOL has worked on automatic speech recognition, neural machine translation and text-to-speech models for more than 30 languages. When it came to bringing 10 languages to Galaxy AI, this expertise meant the team was well suited to seamlessly blend cultural perspectives with Samsung’s global technology.
SRPOL has years of experience in Natural Language Processing. What makes it unique is its adaptability to work on any language thanks to the passionate team and their tools, such as a crowdsourcing platform that enables fast and agile development.
“Collaboration across the continent means relentless data collection, annotation and research, which has become something we really enjoy,” says Kornel Jankowski, Head of Speech Decoding at SRPOL. “We’ve dealt with so many languages that our team developed universal, language-agnostic skills. When we’re asked to support a new language model, everybody’s attitude is: Oh wow, we get to learn another one, that’s going to be fun!”
A European Center for AI Language Development
Language is a cornerstone of culture and communication across Europe regardless of whether it’s incorporated into technology. However, it presents unique challenges for the team at SRPOL, who develop AI models for European languages.
“Each language and the culture that it is part of, comes with hurdles that make us reevaluate how we perceive a specific issue,” explains Adam Ros, Head of Artificial Intelligence at SRPOL. These hurdles include navigating the untranslatability of certain phrases and handling idiomatic expressions that may not have direct equivalents in other languages.
The team saw these challenges as an opportunity to make SRPOL a European center for AI language development. The biggest benefit of this is that it shortens the communication path between different departments and crucially, the decision-making path. Whether it is a matter of automatic speech recognition, neural machine translation or text-to-speech, teams could simply walk over to colleagues in Mobile Quality Assurance and efficiently solve problems together.
While this has helped, it hasn’t overcome all AI challenges. Inevitably, there are limitations in AI models when dealing with multiple European languages, such as translating without context or variations in intonation. However, the team saw these as an opportunity to keep learning and innovating.
“My team never stops at just one example when handling a new word or topic. Some European languages are harder than others,” adds Ros. If you’ve ever been to Spain, you know that Spanish is often spoken at blazing-fast speeds and we need to train AI well to handle that.”
Galaxy AI’s expansion required novel cross-continent collaboration, but the work soon grew beyond European borders. SRPOL supported the Jordan team’s efforts to teach Galaxy AI Arabic’s myriad of dialects, as well as the Brazil team’s work on Latin American languages.
The importance of language and cultural difference subtleties are all on the radar of SRPOL product developers because they can all be noticed by the target — the end users.
“There are subtle differences between European cultures that impact whether something feels natural to the end user. For example, people in some countries expect to read prices with the euro symbol (€), while others are accustomed to seeing it spelled out, e-u-r-o-s,” says Agata Maria Rozycka, Head of Voice Intelligence Research at SRPOL. “If this cultural nuance is not reflected translated text, the interface might seem less intuitive to a user. Implementing these micro-level insights into interface design can make technology feel more natural across diverse cultures.”
“The team has been remotely communicating and collaborating across different countries for many years, building up numerous effective communication channels,” says Marcin Mrugala, Head of Mobile Quality Assurance at SRPOL. “We were ready to do our part in enabling Galaxy AI to lower language barriers around the world.”
Technology for Bridging Cultures
Managing and integrating diverse linguistic and cultural insights is a challenging task, but it is essential for Samsung’s vision for Galaxy AI — lowering the barriers that divide people based on language and culture, and enabling them to create deeper connections.
“We’re not just building technology of the future, we’re building teams of the future too. Our best practices are designed to refine products based on differences across countries, but we fundamentally believe our similarities far outweigh our differences and our technology can unite cultures,” says Mrugala.
“Our goal is to bring people together, to make their lives easier, and to simplify their daily tasks. We’re seeing our families using the Voice Recorder in new ways, and we can now call our friends and different countries and talk with them in their own language. It is magical to see this change in the world and to be part of it. Galaxy AI brought SRPOL people together and now we are bringing together the world,” concludes Rozycka.
This article was first published at Source link . You can check them out for other stuffs