When considering digital recording and digital playback sound quality depends on the range of sound signal, the rate at which it is sampled, and various conversions that occur in sound reproduction system. In lossy codecs like MP3, sound quality is a factor that determines how much of the sound signal data the encoder is allowed to loose in order to reduce file size. In MP3-encoded signals for instance the quality is defined by its bitrate, in kilobits per second (kbit/s).

The frequency range of sound (in Hertz) which equipment is capable to sample and reproduce affects sound quality. Humans can hear frequencies ranging from about 20 Hz to approximately 20 kHz, so sampling that does not extend far enough will take effect on the sound quality.

Sound signal wave is continuous and has some real value at every instant. The digital quantization of the analogue sound wave means that much of the continuous sound wave is not recorded. The rate at which the sound is sampled refers to the amount of information the detection equipment records for each second of the sound. The higher the sampling frequency, the more accurate the final samples will be. However, there is a mathematical proof that in order to preserve all frequencies in the original sound it’s enough that the sampling frequency is two times higher than the highest frequency in the sound signal spectrum. Thus for example when dealing with speech one can easily use sampling frequency of 8kHz, because human speech spectrum is limited by 3.4kHz.

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For each fragment we determine integral spectrum by using discrete cosine transformation (DCT). Spectrum integration is calculated according to the proprietary formula. In the spectrum calculation the interpenetration of windows comes to N/2 samples, and the Hamming or Blackmann-Harris window function is applied to every window. Levels of spectrum energy on bands are determined for all sets of bands. Groups of critical bands, determined by different authors resulting from different models of sound perception and speech production.

Band boundaries (initial and terminal indices) as well as band energy values we determine by a set of proprietary formulas. The initial quality estimation value is taken as 100%, which decreases proportionally to distinction of energies on bands. The most interesting fact is that we can scale down our percentage of signals similarity to the well-known Mean Opinion Score (MOS) values, which correspond in tests to Cisco MOS or ITU P.862 as precise as 97%. More interesting facts to follow – stay in touch!