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SYNTHESIZING MEDICAL TERMS – QUALITY AND NATURALNESS OF THE DEEP TEXT-TO-SPEECH ALGORITHM

Abstract

The main purpose of this study is to develop a deep text-to-speech (TTS) algorithm designated for an embedded system device. First, a critical literature review of state-of-the-art speech synthesis deep models is provided. The algorithm implementation covers both hardware and algorithmic solutions. The algorithm is designed for use with the Raspberry Pi 4 board. 80 synthesized sentences were prepared based on medical and everyday language employing the TTS algorithm. For tests, an application is built, containing a questionnaire allowing for evaluating the quality and naturalness of the synthesized speech, for both types of language. It is followed by the algorithm efficiency tests. A presentation of the performed tests, along with the results obtained from 30 respondents, is shown. The discussion consists of a statistical analysis of the obtained results and a comparison with other speech recognition solutions used as a reference. Finally, in the summary section, there is an overall conclusion of this approach and promising directions for future development. This work is supported by the Polish National Center for Research and Development (NCBR) project: “ADMEDVOICE-Adaptive intelligent speech processing system of medical personnel with the structuring of test results and support of therapeutic process,” no. INFOSTRATEG4/0003/2022.

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Accepted or Published Version
DOI:
Digital Object Identifier (open in new tab) 10.1121/10.0023270
License
Copyright (2023 Acoustical Society of America)

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Category:
Articles
Type:
artykuły w czasopismach
Published in:
Journal of the Acoustical Society of America no. 154, pages 1 - 9,
ISSN: 0001-4966
Language:
English
Publication year:
2023
Bibliographic description:
Kostek B., Szyca B.: SYNTHESIZING MEDICAL TERMS – QUALITY AND NATURALNESS OF THE DEEP TEXT-TO-SPEECH ALGORITHM// Journal of the Acoustical Society of America -,iss. 154 (2023), s.1-9
DOI:
Digital Object Identifier (open in new tab) 10.1121/10.0023270
Sources of funding:
  • Free publication
Verified by:
Gdańsk University of Technology

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