This article describes common approaches to frequency and notes recognition on mobile devices and demonstrates advantages of YIN algorithm for solving this problem. Considering the fact that mobile devices have less memory and less processor power, it is important to find a solution that allows performing computation with low resource requirement. In addition, for proper musical notes fetching the fast run-time environment is needed. Usually Fast Fourier Transformation is used for solving this problem but it has to perform many difficult mathematic operations that may take a lot of time. This article proves practicability of using a different method — YIN algorithm. The YIN was invented by Alain de Cheveigne and Hideki Kawahara in 2002 as an alternative to well-known methods such as Fast Fourier Transformation (FFT). This algorithm is based on autocorrelation method with several essential improvements which makes it possible to decrease error probability in acoustic signal processing. As at the moment of writing there are no applications for Android OS that could reliably perform frequency to notes transformation with following music sheet creation, an attempt was made to develop such an application. This paper describes application architecture and provides detail about the responsibility of each module. Article presents comparison of YIN and FFT algorithms based on speed that was measured on an Android device with multiple input acoustic signal configurations. These results prove the practicability of YIN usage as it provides faster calculation with less memory resource consumption.