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The work considers a software package for automating speech quality assessment. The complex is used for speech rehabilitation of patients after surgical treatment of oncological diseases of the organs of the speech-forming tract. The structure of the complex and the role of its individual modules are presented. The complex has been introduced into the activities of the Oncology Research

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The paper proposes a method to solve the task of automated quantitative assessment of the syllable pronunciation. This quantitative assessment is used to evaluate the speech quality during speech rehabilitation. An algorithm for quantifying the similarity of two audio signals of different lengths is presented. The algorithm uses a hybrid match measure. The hybrid measure is based on calculation of three metrics (DTWdistance, correlation coefficient and Minkowski metric) and using a fuzzy classifier as a mechanism for combining the calculated values. The average number of coincidences of estimates by the proposed algorithm and estimates by the previously applied method is 83%. A method for quantifying the similarity of speech signals using several reference signals is proposed. The method allows to consider the variability of speech and the individual characteristics of the phoneme’s pronunciation. This is achieved by using records of the patient's preoperative speech as reference signals.

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