Wavelet Voice Sonogram vs Audio SA Kullanım & İstatistikleri

"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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"Audio SA" is a spectrum analyzer that can capture voiceprints as TFFT images. The created TFFT image can be exported as a high resolution image. (Image size example iPhoneSE3: 4096×4096, iPhoneX: 6144×6144) If you just want to try creating a voiceprint, you don't need to worry about the settings. Just record your voice and run the TFFT to see the voiceprint. "Audio SA" can also be used for FFT-related learning. You can also check changes in important characteristics such as FFT frequency resolution and dynamic range while switching the FFT size and window function. As an additional function, we have implemented a simple waveform generator, so please try it when learning. The simple waveform generator can generate sine waves, square waves, Gaussian white noise, and their combinations. When using TFFT images for machine learning, etc., it will be necessary to give sufficient consideration to the settings. "Audio SA" allows you to set the audio waveform analysis range, FFT size, power spectrum scale, window function, and drawing color. The analysis range of the audio waveform is set by scaling and moving the audio waveform. The displayed range becomes the analysis range. Tap the play button to play only the analysis range, which is convenient for checking. FFT size can be selected from 256,512,1024,2048,4096,8192,16384,32768. (However, you can select from 256, 512, 1024, 2048, and 4096 during recording and playback.) The power spectrum scale can be selected from Linear scale, Log scale, and Mel scale. For Mel scale, you can set the break frequency. The mel scale is close to a linear scale up to the break frequency and close to a log scale after the break frequency. 700Hz, which is the most commonly used frequency, is set as the default value. The window function can be selected from Blackman, Hamming, Hann, Rectangular. It is recommended to choose Blackman when wide dynamic range is required and Hamming when high frequency resolution is required. Roughly speaking, Hann is a trait between Blackman and Hamming. For Rectangular, no special window function is multiplied during FFT transform. The audio data cut out from the audio waveform for the FFT size is used as it is. In addition, the lower limit of the dynamic range when drawing TFFT images can also be set. It's easy to set up, just swipe up and down on the FFT image. The part displayed as the FFT image is drawn as it is in the TFFT image. "Audio SA" consumes tickets to record audio. Tickets can be earned by watching ads. However, if you purchase "Remove Ads" as an in-app purchase, you will be able to record without a ticket. [details] https://app.brain-workout.org/spectrumanalyzer-e/
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Wavelet Voice Sonogram VS.
Audio SA

Aralık 17, 2024