Comparison

Low Frequency Detector vs Sound Spectrum Analysis

Price, ratings, monetisation and update history for both apps, side by side — with what reviewers say about each.

Head to head
About

Low Frequency Detector

This tool measures and analyzes low-frequency sounds that are difficult for the human ear to detect. It helps identify potential noise pollution from sources like construction or factories, providing detailed reports on frequency components and sound levels.

Highlights
  • Low-frequency power level measurement (<100Hz)
  • Audible band power level measurement (Leq)
  • 1/3 octave band analysis (OCT)
  • FFT analysis (FFT)
  • Time course graph (TIME)
  • Measurement report generation
  • Calibration function
Read full description

"Low Frequency Detector" is an acoustic measurement tool for detecting low-frequency sounds that is hard to hear in normal situation. The human ear is not sensitive enough to low-frequency sounds. If you are exposed to noise from nearby construction or factories without realizing it, you may feel discomfort or a sense of pressure. In such cases, you can use this app to check what kind of low-frequency noise is present. Generally, low-frequency sounds is a sound wave ranging from 1Hz to 100Hz. Depending on its frequency component and sound level, the degree of influence on the human body and the noise sensation is different. This app allows you to examine the frequency component of low-frequency sounds by 1/3 octave band analysis and FFT analysis. Features: - Low-frequency power level measurement less than 100Hz (LF Level): Flat characteristic, Updating indication of measurement period 1 sec. - Power level measurement in the audible band (Leq): Flat characteristic, Updating indication of measurement period 200ms. - 1/3 octave band analysis (OCT) - FFT analysis (FFT) - Time course graph (TIME) - Snapshot (Snap) on the measurement display screen. - Report function (Report): Analysis report of a peak LF Level with TIME, OCT and FFT. - Measurement time: up to 60 sec Functions: The measurement analysis is performed in the following step. Be sure to set the measurement conditions in Step-1 once before starting the sound measurement. 1) Calibration (Calibrate): The reference signal (1kHz sine wave) is output to determine the reference noise level for the low-frequency component. If the volume level of iPhone is set to about 20-50%, the calibration will automatically adjust it to the optimum volume level for the reference signal. 2) Measurement (Measure): Analyze a power level of low-frequency sounds. - LF Level (dB): Low-frequency power level less than 100Hz. - Leq (dB): Sound power level with the frequency weight characteristic Z (Flat) of the audible band. 3) Measurement display: It can select either 1/3 octave band frequency analysis, FFT analysis or Time course graph. They are updated in real time. 4) Report: Measurement result report. It is effective when measuring for 10 seconds or more. # Time course graph: TIME - Low-frequency (LF) Level (dB): Time course graph with peak level noise level judgment (RED-very noisy, YELLOW-noisy, GREEN-normal) at the peak level. - LF max (dB): maximum dB value of low frequency. # Frequency response graph: OCT, FFT - OCT Band LF max (dB): maximum dB value in 1/3 octave band at LF max observation. - Max Level Frequency (Hz): peak frequency at LF max observation. Notes: - The sound measurement of the low-frequency range is a level difference with respect to the reference signal, which indicates the relative power level. - The reference signal is output during calibration and sound level measurement. - Do not change the volume level of iPhone after the calibration. - White line in the OCT and FFT modes indicates frequency characteristics in frequency weight correction of G characteristics. - Since iPhone's built-in microphone has a lower sensitivity on the very low frequency range, it is not recommended to measure a huge volume sound near a very loud noise source. - Since it takes a while for the observation value to stabilize immediately after the start of measurement, the maximum value is calculated from about 2 seconds later. - In the case high power of 1kHz component is included in the measured noise source, the precision of measured value by this app largely decreases. - Sudden noise or impulsive sounds are not low frequency noises in general. - The previous calibration information can be maintained internally. - The analysis results may vary due to individual differences in iPhone devices. - The authorization to access built-in microphone and Photos will be confirmed by iOS system at first access. Please visit our iOS app support page for more information.

About

Sound Spectrum Analysis

Analyze sound spectrums in real-time using your device's microphone. This tool offers detailed frequency and amplitude scales, various window functions, and octave band analysis. It can also function as a noise level meter and allows for data export and saving of measurements.

Highlights
  • Real-time sound spectrum analysis
  • Fast Fourier Transform (FFT) with adjustable size
  • Linear and logarithmic frequency/amplitude scales
  • Octave band analysis (1/1, 1/3, 1/6, 1/12)
  • Multiple window functions
  • A- and C-Weightings
  • Sound level meter (dB SPL)
Read full description

The application is designed for analysis of a sound spectrum in real time (with a microphone). Besides, the application can be used as a measuring instrument of noise level (not for exact measurements). • Sound wave. • Fast fourier transform (FFT). FFT size: 2048 (the accuracy of determining the frequency of ±12 Hz), 4096 (±6 Hz), 8192 (±3 Hz), 16384 (±2 Hz), 32768 (±1 Hz), 65536 (±0.5 Hz), 131072 (±0.2 Hz). • Linear and logarithmic frequency scale. • Linear frequency scale with maximum details (there is a choice for the displayed frequency range). • Linear and logarithmic amplitude scale. • Octave bands (1/1, 1/3, 1/6, 1/12). • Window functions (Blackman, Hamming, Hann (Hanning), Blackman–Nuttall, Gaussian, Flat top). • A- and C-Weightings. • Peak hold. • Exponential spectrum averaging. • Peak frequency detection. • Values of any point (for frequency scale and sound wave (at maximum detail)). • Sound level meter (dB SPL). You can calibrate your microphone by launching a signal generator with a sinusoid frequency of 1000 Hz on another device and making the volume very low. When the sound is almost inaudible, it is necessary to find the amplitude for the frequency of 1000 Hz on the spectrum (FFT size: 16384). This value should be multiplied by 1.2 (to compensate for spectral leakage). It will be the reference value for your microphone. ESTIMATE THE TOTAL NOISE LEVEL BY USING THE SOUND WAVE MODE AT THE MAXIMUM VALUE. • Sample rate: 48000 Hz. • Taking a screenshot by lightly touching the screen. • Export data to a WAV or text file ("Y=[y1 y2... yn]", "y1;y2;... yn", "x1;y1\nx2;y2;..."). Number of points is adjusted via "FFT size". • Automatic stop in the sound wave mode (when increasing or decreasing signal strength). • Automatic stop in the spectrum mode. Now you can stop data collection when the start of the fading signal reaches the end of the FFT buffer. The beginning of the signal is not calculated accurately (just like with an automatic stop in the sound wave mode). • Test wave. • Saving the measurement results in the application. Files with saved data (SavedData_[date]_[time].txt) can be copied to a desktop/laptop computer or transferred to another iPhone using iTunes. There are buttons for quick loading and comparing saved files. • Dark theme. • List of frequency peaks. If several peaks have a common base, then they are considered as one peak. The minimum height of the peak for octave bands is 2 dB. • Interpolation of frequencies in the list of peaks. To interpolate the frequency of the peak, select the Gaussian window (the accuracy of determining the frequency can increase by 10-100 times). The calculation is not done for the extreme bins or if the adjacent bin is zero. • Calculation of the amplitude (in the list of peaks) using neighboring bins (to compensate for spectral leakage and use of the window). The number of bins used for calculation is written in brackets. • Collecting recent data (last minute). You can move over all collected data. The amplitude of the waveform can be changed in the sound wave mode. • Calibration file. The app recognizes only files for the UMIK-1 microphone, but you can specify which microphones you need support for.

Screenshots

Low Frequency Detector4 screens
Sound Spectrum Analysis4 screens

Verdict

The call

The clearest difference is price: Sound Spectrum Analysis at Free against Low Frequency Detector's $9.99. Sound Spectrum Analysis also leads on rating (3.6 vs 2.8) and update cadence (every 5 weeks vs every 9 months). Low Frequency Detector's advantage is in-app purchases (none vs 1). On ads and device support there is nothing between them.

Scored on Price · Rating · Positive reviews · Number of ratings · Update frequency · Ads · In-app purchases · Monetization · Best chart rank · Devices · Requires iOS

CostPrice · In-app purchases · Ads · Monetization

Sound Spectrum Analysis is free to download; Low Frequency Detector costs $9.99 up front. Sound Spectrum Analysis sells 1 one-off in-app purchase. Low Frequency Detector asks for nothing beyond the download.

ReceptionRating · Positive reviews · Number of ratings

Sound Spectrum Analysis holds the better App Store score, 3.6 against 2.8. That said, the two scores are not equally well evidenced: Sound Spectrum Analysis has 42 ratings behind it against 6, so its average is the more settled of the two. Written reviews point the same way: 50% of Low Frequency Detector's written reviews are positive against 58% of Sound Spectrum Analysis's.

UpkeepUpdate frequency

Low Frequency Detector ships an update every 9 months, Sound Spectrum Analysis every 5 weeks. The most recent releases landed on November 2, 2026 and November 4, 2026 respectively.

Scorecard8 real differences · 2 level
Low Frequency Detector versus Sound Spectrum Analysis: the parameters behind the verdict, then further details
ParameterLow Frequency DetectorSound Spectrum Analysis
Price$9.99Free — better
Rating2.8 (6 ratings)3.6 (42 ratings) — better
Positive reviews50.0% of reviews58.3% of reviews — better
Number of ratings642 — better
Update frequencyEvery 9 monthsEvery 5 weeks — better
AdsNoNo
In-app purchasesNo — betterYes
MonetizationPaidFree with in-app purchases — better
DevicesiPhoneiPhone, iPod — better
Requires iOS26.215.6 — better
Further details — not scored
Size1 MB5 MB
Age rating4+4+
DeveloperTOON,LLCDmitriy Kharutskiy

Customer experience

Low Frequency Detector

All ratings6 ratings
Positive50.0%
Neutral0.0%
Negative50.0%
Written reviews8 reviews
Positive50.0%
Neutral0.0%
Negative50.0%

Sound Spectrum Analysis

All ratings42 ratings
Positive64.3%
Neutral2.4%
Negative33.3%
Written reviews36 reviews
Positive58.3%
Neutral2.8%
Negative38.9%

In-app purchases

None

Low Frequency Detector

No in-app purchases

1 purchases

Sound Spectrum Analysis

One-time1
  • Full version$2.99

Questions

Is Low Frequency Detector free?
Low Frequency Detector costs $9.99, with no in-app purchases.
Is Sound Spectrum Analysis free?
Sound Spectrum Analysis is free to download, with in-app purchases available.
Which has better reviews, Low Frequency Detector or Sound Spectrum Analysis?
Sound Spectrum Analysis is rated higher. Low Frequency Detector averages 2.8 out of 5 from 6 ratings, while Sound Spectrum Analysis averages 3.6 from 42 ratings.
Do Low Frequency Detector or Sound Spectrum Analysis have ads?
Neither Low Frequency Detector nor Sound Spectrum Analysis shows ads.
Which is updated more often, Low Frequency Detector or Sound Spectrum Analysis?
Low Frequency Detector ships an update every 9 months, and Sound Spectrum Analysis every 5 weeks. Most recently, Low Frequency Detector was updated on November 2, 2026 and Sound Spectrum Analysis on November 4, 2026.

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