Morse Decoder AI app icon
Apple App StoreObserved metadata

Morse Decoder AI

Yuriy KvashaUtilities0.00 · 0 ratings
Open store
Publisher
Yuriy Kvasha
Category
Utilities
Version
1.1
Last updated
Jan 8, 2024
Public page · no login requiredMetadata observed Sep 7, 2026, 8:37 PM

Research answer

What AppTrendKit can say about Morse Decoder AI today

Morse Decoder AI has no estimate-backed download or gross-consumer-spend figure that meets the public evidence contract yet.

Observed App Store metadata, chart positions, and history are shown below. Missing, non-finite, undefined-currency, or undefined-metric evidence stays missing rather than becoming zero.

Performance intelligence

Observed trajectory and estimates

Store ranks are observations. Downloads and gross store consumer spend are AppTrendKit estimates and only appear when persisted evidence exists.

Estimated downloads · 30D

Modeled

No persisted estimate

The page does not turn missing evidence into zero.

Estimated App Store gross consumer spend · 30D

Modeled

No persisted estimate

The page does not turn missing evidence into zero.

Estimated downloads · 7D

Modeled

No persisted estimate

The page does not turn missing evidence into zero.

Estimated App Store gross consumer spend · 7D

Modeled

No persisted estimate

The page does not turn missing evidence into zero.

Revenue growth · 30D
Download growth · 30D
Grossing rank
Free rank

Evidence history

Collected daily performance

No daily metric history has been persisted yet.

No backfilled days
Daily metrics will appear here after the estimator has persisted more than one observation.

Rank history

Observed chart positions

Lower rank is better. Only collected observations are shown.

No positive rank observations are stored for this storefront yet.

Coverage note

What the ranks mean

A missing rank is not treated as zero downloads or zero revenue. Apple chart feeds are bounded and may return censored or not-ranked observations outside the visible chart depth.

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Storefront mix

Top countries by estimated contribution

Country estimates are aggregated only after country-level predictions exist.

No country-level economics have been persisted for this app yet.

Monetization

Observed store economics signals

Classification
Paid listing
Price
SEK 39.00
In-app purchases
Not observed
Subscriptions
Not observed

These are listing and product observations. They are not company revenue, subscriber counts, or advertising revenue.

App details

Store metadata

Version
1.1
Released
Jan 1, 2024
Last updated
Jan 8, 2024
Content rating
4+
Default storefront
SE

Public IAP observations

Validated in-app purchase prices

Only persisted rows with an explicit public publication boundary are shown. Missing price, currency, country, or date values stay unknown.

Unavailable
No validated public IAP price observations have been persisted for this app yet.

Listing detail

What the store says

The Morse Decoder AI is an application for decoding Morse code signals using artificial intelligence. The application is designed for use by amateur radio enthusiasts for educational purposes. The Morse decoder listens to the audio stream through the microphone or line input and, upon detecting Morse code signals, decodes them into text. The neural network of the application is trained to decode signals with a speed ranging from 10 to 40 words per minute within a frequency range of 200 Hz to 900 Hz. The application supports two modes of operation: direct (default) and tone filtering mode. In direct mode, the neural network will attempt to decipher Morse code signals in the audio range of 250 Hz to 900 Hz. This mode is suitable for confident reception of Morse code at levels of 7db-9db on the S-meter. The tone filtering mode is ideal for decoding Morse code from noisy weak signals in the presence of radio interference. The audio input signal is first filtered using band-pass filters before being passed to the neural network for decoding. This mode allows for the decoding of faint signals, but it requires the accurate specification of the signal's tone frequency. Each radio amateur selects their own CW tone frequency in the transceiver settings, and it is important to tune precisely to the carrier frequency using the ZIN/SPOT button in YAESU transceivers, or the AUTOTUNE button in ICOM transceivers. There are 3 band-pass filter options available: 25Hz, 50Hz, 150Hz. If you can accurately determine the CW signal tone frequency, using the 25Hz filter, you can decode very faint Morse code signals. The application offers two neural network options: A and B, which can be easily switched in the interface. Network A is recommended for use with stable signal transmission with a constant duration of dots and dashes, while network B is recommended when using a straight key, where the duration of dots and dashes may vary. You have the ability to switch between these networks in real time and observe how each network hears and decodes Morse code. It is important to monitor the level of the incoming audio signal, for which the application provides a sound level indicator. Ensure that the signal is not too quiet or too loud. It is recommended to maintain the signal around -7db, which is sufficient for decoding. Keep in mind that higher audio frequencies are quieter than lower frequencies. Additionally, the application provides various color themes, allowing radio enthusiasts to customize the appearance of the application for comfortable use.

Publisher website

Store creative

Screenshots

Morse Decoder AI screenshot 1
Screenshot 1
Morse Decoder AI screenshot 2
Screenshot 2
Morse Decoder AI screenshot 3
Screenshot 3
Morse Decoder AI screenshot 4
Screenshot 4

Competitive set

Similar apps

Deterministic links to real stored apps matched by category, publisher, and comparable performance bands.

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Methodology and provenance

Read every number with its evidence

Metadata source: Apple iTunes Search API; observed Sep 7, 2026, 8:37 PM.

Rankings: collected chart positions from the listed storefront. Missing ranks are not zeros.

Economics: downloads and gross store consumer spend are estimated, not official Apple or publisher figures.

Model: No persisted model version.

Confidence: ; intervals widen when evidence or history is limited.

Last observation: Sep 7, 2026, 8:37 PM.

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