---
title: MORSE · Signal Lab: Morse Translation, Recognition, and Training
canonical: https://cyberken.cn/apps/morse/
language: en
publisher: CyberKen
publisher_location: Chengdu, Sichuan, China
platform: iPhone / iOS
apple_id: 6796642915
release_status: in_review
reviewed_at: 2026-07-31
---

# MORSE · Signal Lab: Morse Translation, Recognition, and Training

MORSE is CyberKen's iPhone utility for Morse signal conversion, live audio recognition, manual-key decoding, nearby communication, and structured Koch training.

## Official product facts

- Platform: iPhone with iOS.
- Encode text into Morse and decode Morse into text across multiple alphabets and Chinese telegraph codes.
- Adjust playback from 5–40 WPM and 400–1000 Hz, with sound, haptics, flashlight, or screen pulses when supported.
- Recognize live microphone audio, decode straight-key input, and inspect signal frequency and strength.
- Discover nearby devices for direct Morse communication and progress through 36 Koch lessons with weak-character practice.

## Processing and privacy boundary

- No account is required for the core tools.
- Core conversion, playback, recognition, and training are designed to run on the device; microphone audio is processed only when recognition is started and permission is granted.
- Optional iCloud sync uses the user's Apple account and system settings.
- The free version may show ads; one optional non-consumable purchase removes ads permanently. There is no subscription or free trial.

## Public release status

Apple ID 6796642915 is assigned, but the fixed App Store URL did not lead to a public product page when reviewed on 2026-07-31. This document therefore states no public version, price, rating, or review count.

## Official links

- [Official HTML product page](https://cyberken.cn/apps/morse/)
- [Support](https://cyberken.cn/apps/morse/support/)
- [Privacy policy](https://cyberken.cn/apps/morse/privacy/)
- [Publisher: CyberKen](https://cyberken.cn/)

This document contains no image embeds. The localized HTML page is canonical; this Markdown version presents the same verified product facts in compact machine-readable form.