Wavelet Voice Sonogram

N/V

Veröffentlicht von: TOON,LLC

Beschreibung

"Wavelet Voice Sonogram" is a new sound spectrogram app that performs time-frequency analysis of acoustic signals.
A spectrogram is a graph that shows the results of a sound frequency spectrum analysis with time on the horizontal axis, frequency on the vertical axis, and signal strength in colors.
This app can perform acoustic analysis and display the spectrograms by using three time-frequency analysis methods, Wavelet analysis, Octave Band analysis, and FFT analysis.
It can record sounds from iPhone's built-in microphone. While playing the sound, you can search for the desired sound and analyze it.
"Wavelet Voice Sonogram" allows you to easily perform acoustic analysis of speech, instrumental sounds, noise, and more. It can also be used to learn elementary speech analysis.
Features:
- Acoustic analysis can be performed using PCM data recorded with the iPhone's built-in microphone. It is possible to analyze 5 seconds of sound data backward from a user-specified point in time.
- Three types of acoustic analysis, FFT analysis, octave band analysis and wavelet analysis, can be performed simultaneously.
- PCM sound recording and playback is possible up to about 180 seconds, and the audio waveform graph and FFT analysis graph are displayed. While playing back sound, you can search for sound at any point in time.
- Zoom in on a specific 10 seconds of PCM data and play back the sound. Used to find a specific sound at the point in time you want to analyze.
- The spectrogram analysis result and time axis waveform can be contrasted and played back.
Specifications:
- Sampling frequency: 48 kHz
- PCM recording time: approx. 180 seconds max.
- Sound zoom function (10-Sec): Zooms in on any 10 seconds of PCM data and plays back the sound.
- 3 types of acoustic analysis function (Analysis): About 5 seconds (Analysis points can be specified using the Time position slider.)
-- FFT analysis (FFT): FFT 2048 points
-- Octave band analysis (OCT): 1/48 octave band
-- Wavelet analysis (DWT): Gabor Wavelet
- Sound recording and playback, sound waveform and FFT graph display (Main): PCM graph, 10sec zoom graph, FFT graph.
- Time position slider: Points to the cursor position on PCM graph.
- Spectrogram display (FFT / OCT / DWT): 5 sec PCM graph and spectrogram analysis graph (vertical axis - time [0 - 5.0 sec], horizontal axis - frequency [100Hz - 8kHz])
- Snapshot (Snap): Save the analysis image in "Photos".
Notes:
- The analysis time varies greatly depending on the performance (generation) of your iPhone. It may take about 5 to 20 seconds.
- Wireless (Bluetooth) headphones and headsets are not supported.
- The first time the app accesses the built-in microphone and Photos after installation, the iOS system will ask you for permission to access them. If you have not enabled this setting, the application will not be able to access them due to iOS system privacy restrictions. Please enable the access permission in the iOS setting "Settings > Privacy & Security > Photos or Microphone".
Please visit our iOS app support page for more information on this app.
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Wavelet Voice Sonogram Häufige Fragen

  • Ist Wavelet Voice Sonogram kostenlos?

    Wavelet Voice Sonogram ist nicht kostenlos (es kostet 2490.00), enthält jedoch keine In-App-Käufe oder Abonnements.

  • Ist Wavelet Voice Sonogram seriös?

    Nicht genügend Bewertungen, um eine zuverlässige Einschätzung vorzunehmen. Die App benötigt mehr Nutzerfeedback.

    Danke für die Stimme

  • Wie viel kostet Wavelet Voice Sonogram?

    Der Preis von Wavelet Voice Sonogram beträgt 2490.00.

  • Wie hoch ist der Umsatz von Wavelet Voice Sonogram?

    Um geschätzte Einnahmen der Wavelet Voice Sonogram-App und weitere AppStore-Einblicke zu erhalten, können Sie sich bei der AppTail Mobile Analytics Platform anmelden.

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Wavelet Voice Sonogram Bewertungen

Completely useless.

AdtGobeldygook on

Südafrika

Need app for instrument acoustic analysis. This app doesn’t even do the most basic testing and very poor definition. Waste of money.

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