Elements of Methodology of Precision Phonetic Analysis of Oral Phonograms
DOI:
https://doi.org/10.31649/1997-9266-2022-162-3-36-51Keywords:
computer linguistics, classification of language units, automated transcription, phonetic analysis of speechAbstract
The study of the cornerstone of modern linguistics - the process of speech and textual interpersonal communication, given the size of the infosphere of the twenty-first century, is impossible without a sound and purposeful involvement of information technology from other fields of knowledge, including computer science. The resulting relatively young science, computational linguistics, aims to automatically analyze natural languages in all spectra of their implementations. Among the long list of topical issues actively studied in the paradigm of computational linguistics, we mention the automation of compilation and linguistic processing of language corpora, automated classification and abstracting of documents, creating accurate linguistic models of natural languages, extraction of factual information from informal linguistic data. An effective, strictly formalized methodology for computational phonetic analysis of linguistic information, especially speech information, is potentially a driving force for improving the results of solving these research problems. This thesis is fully consistent with the content of the article, which proves the relevance of the presented scientific and applied results. Accordingly, the paper presents elements of the methodology of precision phonetic analysis of phonograms of oral speech, taking into account the phenomenon of phonetic fusion. The mathematical apparatus of the created methods is based on the provisions of the theory of pattern recognition, information theory and acoustic theory of language formation. This basis provided the basis for a system of analytical formalization of the problem of multicriteria of the process of recognition of language units of human speech. As a result, a method for reliable clustering of personal phonetic alphabets of speakers is presented. A method for detecting potentially unreliable classified speech units and adjusting the results of the process of automated transcription of speech signals is also presented. A method for estimating the influence of the medium of propagation of the studied speech signals on the transcription result is also proposed.
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