WWDC 2025: Why Apple Chose Live Translation Over Siri?

The most attention-grabbing moment at Apple’s WWDC 2025 wasn’t the highly anticipated evolution of Siri, but the prominent unveiling of the new Live Translation feature. As someone building a real-time translation and interpretation copilot, this move signals something deeper than just a feature update—it reflects a shift in both technological direction and user experience strategy.

Apple’s decision to hold off on showcasing Siri and lead with Live Translation appears deliberate. According to post-WWDC interviews with Apple executives, Siri's new AI capabilities hadn’t yet reached the reliability and polish needed for launch. In contrast, Live Translation was seen as a feature that could deliver immediate value to users. At the same time, this choice reveals how real-time language technologies are no longer peripheral but becoming central to the core user experience.

Apple and Samsung: Entering the Real-Time Translation Space

At WWDC, Apple introduced Live Translation as a deeply integrated, bidirectional translation feature built into the Phone, FaceTime, and Messages apps. It enables users to hear the other person’s voice in their own language during a call and have their own speech translated back—all powered by on-device processing. Apple's signature strengths in consistent UI and privacy-focused design are clearly present.

WWDC 2025 demo showing Apple’s Live Translation across Messages, FaceTime, and Calls.

Samsung, meanwhile, had already commercialized real-time call translation with the Galaxy S24 series. It supports third-party apps like WhatsApp and Google Meet, and even includes voice synthesis that mimics the user’s voice for translated output. If Apple is now formally entering the space, Samsung has been actively experimenting with it across different communication environments.

Samsung demonstrates real-time voice translation during a phone call using Galaxy AI.

But Still, Limited Real-World Adoption—Why?

Samsung has already launched its real-time call translation feature, while Apple has only just announced it. Yet, despite these developments, actual usage of such features remains limited, especially in professional or global meeting contexts. Why is that?

• Limited usage environments – These features are largely confined to specific devices and ecosystems. Samsung offers limited third-party integration, while Apple’s Live Translation is designed to work only within its own apps (Phone, FaceTime, Messages). Integration with real-world collaboration platforms like Zoom or Microsoft Teams is currently unavailable or difficult.
• Language and context limitations – On-device AI offers privacy and faster response times but is constrained by hardware limitations. This restricts its ability to handle long-form context, support diverse languages and dialects, and deliver personalized adaptation.
• Complex meeting dynamics – Real-time conversations in meetings often involve rapid exchanges, domain-specific terminology, and multi-party dialogue. Current AI solutions still struggle to process this level of complexity smoothly.

In short, while the technology is impressive, it hasn’t yet matured into a trustworthy, practical tool for real-world communication needs.

Interpreting for Real Use: The Next Step for Translation Tech

Deeptrue in action: Real-time translation and smart reply suggestions during a multilingual video meeting.

At Deeptrue, we’re addressing these gaps by developing a product that makes real-time communication more practical and flexible:

• High-performance processing for low-latency interactions – We leverage cloud-based GPU infrastructure to minimize delays and continuously optimize audio and text processing speeds.
• Context-aware AI suggestions – Beyond raw translation, our AI understands conversational flow and draws on user-defined instructions to suggest natural, situation-appropriate expressions.
• Cross-platform usability – Built as a desktop app with a transparent overlay UI, Deeptrue works seamlessly with major video conferencing tools like Zoom, Teams, Google Meet, and Webex—without interfering with existing interfaces.

Our goal isn’t just to create an environment where users can "speak without knowing the language," but to help them "say what they want to say, better." Interpretation isn’t just about converting text—it’s about accurately and naturally conveying intent.

Real-time interpretation technology should act as a language copilot: not just a translator, but a companion that helps users speak more confidently and expressively.

What Comes Next for Real-Time Translation?

Announcements from Apple and Samsung make one thing clear: real-time language technology is moving from experimentation into mainstream experience. Still, major technical challenges remain—limitations of on-device AI, the complexity of live dialogue, and the lack of integration with collaborative platforms.

At Deeptrue, we’re facing these challenges head-on. Rather than just speeding up translation, we aim to make real conversation possible. As the technology evolves, we believe the true impact will come not from novelty, but from delivering genuinely useful language experiences to people everywhere.