ОБЩАЯ МЕТОДИКА ВЫСОКОЭФФЕКТИВНОЙ ДИАГНОСТИКИ СЛЕДОВ МОНТАЖА В ЦИФРОВЫХ ФОНОГРАММАХ. GENERAL METHODOLOGY OF HIGH-EFFICIENCY DIAGNOSTICS OF TRACKS OF EDITING IN DIGITAL PHONOGRAMS
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Date
2019
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Abstract
Into the complete set of tools necessary for the judicial technical examination of materials and apparatus of the audio recording, the programs and methodologies (tool) for diagnostic researches of authenticity of phonograms are obligatorily included. Diagnostics of authenticness of phonograms unites researches of originality (i.e. to priority) of phonogram and presence (or absence) in it the tracks of editing. Presently for the record of the phonograms the digital apparatus of the audio recording is mainly used, and editing is produced with the use of digital processing of the signals fixed in phonograms. Therefore there is an insistent necessity of creation of tool for the exposure of tracks of digital treatment (tracks of the digital editing) in phonograms. It is offered by us, along with the instruments worked out before, to apply the neuron networks of the deep learning for creation of the expert tool intended for the exposure of tracks of digital treatment in phonograms. Preliminary researches are completed, and the first version of the program of such high-efficiency system is built. An aim of the study is the creation of general methodology of examining of the authenticity of digital phonograms, based on the tool worked out by authors. In the construction of such system it is suggested to come from that for editing phonogram it is possible from different pre-product – phonograms taped on the different apparatus of the audio recording, and phonograms, taped on one apparatus. For the exposure of tracks arising up at such types of editing, it is necessary to use a different tool, that allows considerably to shorten labour intensiveness and time of examination. For diagnostics of editing, made from the records taped on different apparatus, it is expedient to use the tool built on the basis of fractal approach, in particular, the automated tool is “Fractal”. For diagnostics of editing, made from the records taped on one apparatus of the audio recording, it is expedient to use the tool built on the basis of neuron network of the deep learning. Both types of tool are worked out by authors. Such approach allows to bring down labour intensiveness and time of examining.
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Keywords
звукозапис, справжність фонограми, цифрова фонограма, експертиза справжності фонограм, audio recording, authenticity of phonogram, digital phonogram, examination of authenticity of phonograms