Apple AirPods treten in den Markt der Übersetzungsohrenhörer ein. Steht Timekettle vor einem großen Problem? Das muss keine schlechte Sache sein.

The AI headphones are so popular that even Apple can't sit still.

In iOS 26 Beta 6, Apple quietly hid a significant "surprise" - in the resource files of the system translation app, an image material of AirPods surrounded by "Hello" in multiple languages was exposed, and the file name is even more straightforwardly called "Translate".

Image source: Apple

Combined with Apple Intelligence's layout in real - time translation for calls, messages, and FaceTime in the past two years, it's almost certain that Apple will provide face - to - face real - time translation capabilities for AirPods. In more familiar terms, Apple is going to turn AirPods into a "translation headphone".

In fact, Apple is not the first brand to "upgrade" ordinary TWS headphones into AI translation headphones with the phone's AI capabilities. Domestic phone brands such as Xiaomi, OPPO, and Huawei all have similar AI capabilities.

But the problem is, creating a translation headphone is not as simple as "equipping the headphone with a translation app".

How difficult is it for a regular headphone to become a translation headphone?

First of all, the working logic of common TWS headphones is not designed for high - intensity dialogue scenarios such as AI translation. Recently, Xiaolei had an exchange with an engineer from a translation headphone brand. He said that "many TWS headphones were not designed with the possibility of microphone duplex in mind. Only the microphone of one headphone works during a call", and this single - mode sound - collection working method is naturally not suitable for the AI translation scenario of face - to - face dialogue.

Of course, brands can also change the working mode of the headphones through driver upgrades, allowing the two headphones to process the upstream and downstream sound sources simultaneously in parallel. However, there is also the challenge of microphone noise reduction in front of TWS headphones.

Image source: Apple

Different from the long - term efforts of various brands in active noise cancellation (ANC), mainstream headphone brands pay relatively limited attention to the "upstream noise reduction" of microphones, that is, sound - collection noise reduction. As long as they can distinguish the close - range human voice from the distant environmental noise, they think it's okay.

But translation headphones are different - based on the dialogue scenario, translation headphones will "simultaneously" pick up the voices of both parties in a close - range conversation. As we mentioned just now, a good translation headphone needs to have the ability to process two audio streams (each person's speech) simultaneously with the two headphones respectively, which means that translation headphones need to "rewrite" the sound - collection and noise - reduction logic of regular TWS headphones.

Otherwise, the entire translation link of the conversation will be fragmented by noise interference - for example, at a noisy exhibition site, the voices of both parties will be picked up by the same - side microphone. The AI model has to "separate" the voices of the two people first before it can perform correct translation and broadcast. If the noise - reduction algorithm cannot accurately identify and isolate the sound sources of both parties, the translation result will definitely be problematic.

This is why professional translation headphones like Timekettle are equipped with independent sound - pickup and noise - reduction channels for the left and right ears at the hardware level, and achieve "listening and translating simultaneously" through a duplex architecture - it can not only ensure that the two wearers don't interfere with each other when speaking simultaneously but also stably transmit each person's voice stream to the translation engine for processing.

In addition, professional translation headphones often make a lot of customized designs in terms of microphone array layout, directivity optimization, and sound - source separation of near - field and far - field, and these changes cannot be easily supported by the hardware foundation of ordinary TWS headphones.

The more realistic challenges lie in battery life and latency. AI translation is a continuous and high - computational task. Especially in the local + cloud hybrid inference mode, it requires a stable and high - speed connection between the headphone and the phone in data transmission and processing. This not only tests the Bluetooth link of the headphone but also puts forward high requirements for power consumption control - regular TWS headphones tend to overheat and lose power quickly during long - term high - load operation, which is almost unacceptable for business travelers who need to use them continuously throughout the day.

It's certain that if AirPods enter the translation headphone field in their current form and only rely on the AI capabilities of the iPhone without making special adaptations for duplex sound - pickup, sound - collection noise reduction, and battery - life optimization, they may only meet the temporary translation needs in mild, short - term, and quiet environments and are difficult to replace professional translation headphones designed for high - frequency and multi - scenario communication.

AirPods' entry will promote the popularization of translation headphones

Considering the current situation where the "translation headphone" market is mixed, with high - end products like Timekettle and Youdao competing with "AI translation headphones" priced at around 100 yuan, in the view of Lei Technology, AirPods' entry is very likely to become a watershed in the market.

On the one hand, Apple's advantages in brand trust, user base, and ecological integration are sufficient to significantly lower the public's cognitive threshold for translation headphones in a short period, allowing more users who have never considered such products before to directly experience the convenience of "cross - language communication just by wearing the headphones". This user - education effect will, in turn, accelerate the popularization of the entire category.

Image source: JD.com

On the other hand, this popularization will quickly worsen the situation of low - end translation headphones. Previously, entry - level products that mainly focused on "low price and sufficient functionality" mainly served mild users who occasionally travel abroad and occasionally need cross - language communication. But when AirPods provide a smoother and more stable system - level experience in these mild scenarios, and there is no need to spend extra money on new devices, the core competitiveness of low - end products will almost instantly evaporate.

Moreover, Apple's ecological synergy means that the translation function can be integrated with iOS calls, Siri, and other native services. This convenience cannot be easily replicated by low - end manufacturers.

However, this doesn't mean that high - end brands will be completely replaced. AirPods' entry actually further highlights the value of professional translation headphones: more accurate duplex sound - pickup, stronger voice separation and noise - reduction algorithms, longer battery life, and stable performance in extreme application scenarios such as noisy environments, multi - language accents, and complex conversations. These technological barriers are difficult to be filled by TWS products in a short time and are also the moat of the high - end market.

The future competition is likely to show a polarized pattern of "mild users being absorbed by AirPods and high - frequency users concentrating on professional brands". In other words, AirPods will capture low - end users, while high - end brands will have the opportunity to deepen differentiated competition in a more concentrated niche market.

Deeply binding with AI is a compulsory course for high - end translation headphones

From the development trend of translation headphones, "being associated with AI" has become the core competitiveness of high - end translation headphones. In the past, translation headphones mainly relied on traditional voice recognition and cloud - based machine translation technology. The functional boundaries were relatively fixed, and the update and iteration rhythm was slow.

In the era of large models, the emergence of technologies such as LLM and multi - modality has brought a qualitative improvement to high - end translation headphones in terms of semantic understanding, context reasoning, and multi - round dialogue connection. This not only improves the translation accuracy but also makes the headphones more flexible in cross - scenario applications.

For high - end brands, this ability is not only a product selling point but also the foundation for maintaining premium and market position - once the AI ability lags behind, it will directly affect the final user experience. After all, in professional scenarios such as international business, academic conferences, and foreign - language interviews, accurate and smooth translation is both a rigid requirement and a competitive barrier that ordinary TWS headphones cannot easily replicate.

Image source: Timekettle

Lei Technology believes that future high - end translation headphones must regard AI as the core driving force for product iteration. Only in this way can they retain their core user group under the popularization impact brought by AirPods and continue their advantages in a more niche and high - value market.

To put it more directly, to become the real king in the translation headphone field, one must first "win the competition against AirPods" in the AI field.

This article is from the WeChat official account "Lei Technology". Author: Lei Technology AI Hardware Team. Republished by 36Kr with authorization.