techkritiko@gmail.com (Jay Bonggolto)
2025-08-28 13:52:00
www.androidcentral.com
What you need to know
- The Honor Magic V5’s translation happens entirely on your phone, so your calls stay private.
- Six full language packs are squeezed into just 800MB, meaning no more wasting gigabytes of storage.
- You don’t have to wait for full sentences; the AI translates as you speak.
You know that feeling when you’re on a phone call and need to translate what someone is saying, but you’re worried about your private conversation being sent to the cloud? Honor has introduced a new solution to this common problem with its latest flagship phone, the Magic V5.
Honor’s new technology brings real-time, on-device translation to your device. What makes it different? Everything happens on the phone, eliminating the need for cloud solutions. That means better privacy, lower latency, and no internet dependency.
Two technical papers backing the tech were also accepted at INTERSPEECH 2025, a major conference on speech processing.
While some on-device translation has existed before, it often falls short in terms of speed, accuracy, and memory usage. Honor’s latest approach changes that, delivering cloud-level performance while keeping everything private and stored locally on your phone.
This leap forward comes from cracking tough problems in on-device multilingual speech recognition and translation.
One of the biggest hurdles for on-device AI is memory use. Typical translation models can eat up 3–4GB of space. Honor says its solution slims that down to just 800MB, or a 75% reduction, while still packing support for six languages: Chinese, English, German, French, Spanish, and Italian.
That also means you aren’t downloading half a gigabyte per language.
Real-time translations that actually feel real-time
But the real improvement is in how it works. Instead of waiting for you to finish a sentence before translating (the classic way), Honor’s system processes speech in real time, almost like a simultaneous interpreter. The company claims this approach boosts inference speed by 38% and improves accuracy by 16%.
Under the hood, the system uses something called Monotonic Finite Look-ahead Attention, a streaming method that helps the AI predict and transcribe speech without significant delays. There’s also a Parasitic Dual-Scale Modeling technique, developed with Shanghai Jiao Tong University, that helps run large speech models efficiently on phones without compromising performance.
It’s a quiet but meaningful step toward making AI more useful and less obtrusive, especially when you’re trying to have a natural conversation across languages.
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