Simple Guitar tuner Pro - new and awesome IOS app for the iPhone and iPad

By: PRLog
This easy-to-use chromatic guitar tuner is developed for the iPhone and iPad (iOS 8.0 and above) and has a high precision. In addition to the exact frequency, it offers FFT and autocorrelation.
PRLog - June 15, 2015 - MUNICH, Germany -- This guitar tuner is developed for the iPhone and iPad (iOS 8.0 and above), and has the following features:
+ High precision (approximately 0.1 %).
+ Large frequency range (22 Hz to 1000 Hz).
+ Suitable for bass, guitar, ukulele, mandolin, etc.
+ Display of exact frequency (in Hz).
+ Gauge view of the detected (semi) tone and octave.
+ “Tune up/down" (in Hz, marked by up/down arrow).
+ Spectral View (FFT).
+ Time-Domain View (Autocorrelation).
+ “Tuning by ear".
+ User Manual.
+ Available in 11 different languages.
+ Free user support (English, French, Spanish, Portuguese, Italian, German).

You can check out at http://www.simpleguitartuner.com

In addition to the high precision, Simple Guitar Tuner Pro offers a wide frequency range, so that the following instruments can be tuned:

+ Bass (30.87 Hz to 98 Hz).
+ Cello (65.41 Hz to 220 Hz).
+ Contrabass ( 82.41 Hz to 196 Hz).
+ Guitar (82.41 Hz to 329.6 Hz).
+ Viola (130.8 Hz to 440 Hz).
+ Mandolin (196 Hz to 659.3 Hz)
+ Violin (196 Hz to 659.3 Hz).
+ Ukulele (146.8 Hz to 440Hz, depending on tuning).
+ Piano (partially: 27.5 Hz to 987.8 Hz, frequencies above can't be detected with enough precision).

As often misunderstood, pitch and frequency are not the same thing: while frequency is a pure physical quantity, pitch has to do with perception or psychology.

Let's take an example: the low E string of a guitar has a frequency of 82.4 Hz. If you produce a pure sine wave with the same frequency (for example with Audacity), the result will sound artificial and sterile. How do we get the typical sound of an instrument - as for example of a guitar? The keyword is "overtone": every string instrument (guitar, ukulele, mandolin, etc.) produce two different kind of tones: the keynote (thus the tone with the fundamental frequency) and multiple overtones. In addition, it often occurs that overtones are stronger (thus they have a higher amplitude) than the keynote. That's also a reason why frequency detection can be so difficult.

Please take into account that we talk about keynote (or fundamental frequency) when it deals with tuning an instrument (as for example with this IOS app)!

One approach for frequency detection is FFT (Fast Fourier Transformation): here we work with the frequency domain (or spectrum) - the peaks can be associated to the frequencies produced by an instrument.

Another approach for frequency detection is autocorrelation: contrary to FFT, we work with time domain data. As string instruments produce periodic signals, detecting the period of itself can be an appropriate solution. Within autocorrelation, periods of an incoming signal are marked as a peak. Often, we need a number of periods of data to obtain a reliable estimate about the period and thus about the frequency which is inverse to the period.

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