Improved efficiency of digital audio data compression algorithms.
The relevance of the work. Methods for encoding high quality (HS) audio signals have become very widespread in the last decade in the field of broadcasting, digital sound recording, and home audio and video equipment. There’s even a fast-growing new class of consumer electronics: portable MP3 players.
Digital television and radio transmission networks are being developed, providing consumers with high-quality images and sound with a wide coverage area. The popularity of radio and television broadcasts over the Internet and mobile phone networks is increasing. All these technological innovations have become economically viable, and in some cases even technically possible, thanks to the use of highly efficient digital video and audio data compression algorithms, such as MPEG-1 ISO / IEC 11172, MPEG-2 TSO / IEC 13818, MPEG-4 ISO / IEC FCD 14496, ATSC Dolby AC-3. At the same time, due to the economic advantages of using these algorithms, which make it possible to reduce the bandwidth requirements of the transmission channels or the capacity of the information carriers by an order of magnitude, it is necessary to compensate with a certain decrease in the sound quality. During the era of the dominance of digital audio CDs, consumers have created a requirement for high sound quality from any sound reproduction equipment. The efforts of algorithm developers for encoding audio signals have always been aimed at ensuring that the quality of decoded audio material is no worse than that of a CD. Sound quality is often the determining factor in the economic success of digital broadcasting services or digital sound distribution services like iTunes). Further,
It is obvious that the problem of improving the quality of audio coding is today one of the key problems for the sound recording industry, the audio broadcasting industry and the manufacturers of various multimedia systems.
The basic principle of operation of highly efficient audio coding systems is to use the properties of the human auditory system, mainly the phenomenon of masking. The phenomenon of psychoacoustic masking is due to the biophysical and neuronal processing of sound signals by the human auditory system [173]. At the same time, part of the sound information does not affect the acoustic perception of the sound signal due to the presence of components with greater intensity in it. Therefore, the strongest components of the audio signal form the so-called masking thresholds. Sound information with a signal energy level below the masking threshold is not perceived by the auditory system. In the traditional digital representation of audio signals using pulse code modulation (PCM), time-sampled samples of the original signal are represented using a specific number of bits in the code word. The finite precision of the instantaneous values of a continuous analog signal introduces an error in the signal, the so-called quantization noise. The idea of encoding audio signals with the elimination of psychoacoustic redundancy is to combine psychoacoustic analysis and the quantization mechanism of audio signals [112]. In this case, the digitally encoded signal is converted into a time-frequency representation, as close as possible to the time-frequency resolution of the human auditory system. Psychoacoustic analysis determines the masking thresholds at each point in the time-frequency representation of the encoded signal, and the quantizer re-quantizes the signal with the minimum possible number of bits per sample, in which the increasing quantization noise is still below the masking thresholds. Thus, a compact representation of audio signals can be achieved without subjective degradation of sound quality. It is obvious that the efficiency and quality of such systems depend mainly on the precision of the psychoacoustic analysis. a compact representation of audio signals can be achieved without subjective degradation of sound quality. It is obvious that the efficiency and quality of such systems depend mainly on the precision of the psychoacoustic analysis. a compact representation of audio signals can be achieved without subjective degradation of sound quality. It is obvious that the efficiency and quality of such systems depend mainly on the precision of the psychoacoustic analysis.
