Samsung R&D Institute Japan (SRJ) was established as an R&D center focused on hardware such as home appliances and displays. With the demand for AI innovation ramping up globally, SRJ in Yokohama has also been operating a software development lab to create Galaxy AI’s Live Translate, which automatically translates voice calls in real time, since the end of last year.

“Live Translate is particularly efficient for travel scenarios such as visitors to this year’s Olympic Games in Paris,” says Takayuki Akasako, the Head of Artificial Intelligence at SRJ. “We are currently developing a speech recognition program for people who are both sightseeing and watching the Paris Olympic Games; by training the speech recognition program to learn about the games and locations of stadiums for Paris 2024.”

Understanding Context in Voice Recognition

For those already using the translation features of Galaxy AI, such functionalities may seem very useful. But for developers who have made the features come to life, they know that being able to communicate while traveling abroad isn’t something that can be taken for granted.

One thing the team noted was that there are more homonyms in Japanese than some other languages. For instance, ‘chopsticks’ (Hashi,箸) and ‘bridge’ (Hashi,橋) are relatively easy to distinguish due to the difference in intonation, but words like ‘sightseeing’(Kankō,観光), ‘customs’(Kankō,慣行), ‘public’ (Kōkyō,公共) and ‘prosperity’ (Kōkyō,好況) must be judged based on the context.

“Judgement becomes more difficult when the context is ambiguous, such as names of locale and people, proper nouns, dialects and numbers,” says Akasako. “So in order to improve the accuracy of speech recognition, a lot of data is needed.”

“We always look for ways to fine-tune the AI model for key events and moments in a timely manner,” continues Akasako. “With a lot of new combinations of place names and activities, it’s important that the context is still clear when people are using Galaxy AI.”

Challenges in Collecting Efficient Data

While recognizing the types of data needed is also important, collecting the data in and of itself is a challenge in its own right.

Previously, the SRJ team used human-recorded data to train the speech recognition engine for Live Translate, which didn’t result in sufficient data collection.

Samsung Gauss, the company’s Large Language Model (LLM), uses scripts to structure sentences with words or phrases that are relevant to each scenario. The data collected with Samsung Gauss is not only recorded by humans, but also generated by a speech synthesis text-to-speech (TTS) data, through which human resources do the final check on the quality. Using this method, the team has seen a dramatic improvement in data collection efficiency.

“Every time a problem is identified and solved, the accuracy of speech recognition improves significantly,” says Akasako. “Regardless of where people are, our goal is connecting people with each other, and the tools powered by Galaxy AI will ensure more fun and efficient communication.”

Compared to widely used lithium-ion batteries, which utilize liquid electrolytes, all-solid-state batteries support greater energy density, which opens the door for larger capacities, and utilize solid electrolytes, which are demonstrably safer. However, the lithium metal anodes that are frequently used in all-solid-state batteries, are prone to trigger the growth of dendrites¹ which can produce undesirable side effects that reduce a battery’s lifespan and safety.

To overcome those effects, Samsung’s researchers proposed utilizing, for the first time, a silver-carbon (Ag-C) composite layer as the anode. The team found that incorporating an Ag-C layer into a prototype pouch cell enabled the battery to support a larger capacity, a longer cycle life, and enhanced its overall safety. Measuring just 5µm (micrometers) thick, the ultrathin Ag-C nanocomposite layer allowed the team to reduce anode thickness and increase energy density up to 900Wh/L. It also enabled them to make their prototype approximately 50 percent smaller by volume than a conventional lithium-ion battery.

This promising research is expected to help drive the expansion of electric vehicles (EVs). The prototype pouch cell that the team developed would enable an EV to travel up to 800km on a single charge, and features a cycle life of over 1,000 charges.

(From left) Yuichi Aihara, Principal Engineer from SRJ, Yong-Gun Lee, Principal Researcher and Dongmin Im, Master from SAIT

As Dongmin Im, Master at SAIT’s Next Generation Battery Lab and the leader of the project explained, “The product of this study could be a seed technology for safer, high-performance batteries of the future. Going forward, we will continue to develop and refine all-solid-state battery materials and manufacturing technologies to help take EV battery innovation to the next level.”

¹ Dendrites are needle-like crystals that can develop on the anode of a battery during charging.