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

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

Abstrakt

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 albo Published Version
DOI:
Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1121/10.0023270
Licencja
Copyright (2023 Acoustical Society of America)

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Informacje szczegółowe

Kategoria:
Publikacja w czasopiśmie
Typ:
artykuły w czasopismach
Opublikowano w:
Journal of the Acoustical Society of America nr 154, strony 1 - 9,
ISSN: 0001-4966
Język:
angielski
Rok wydania:
2023
Opis bibliograficzny:
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:
Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.1121/10.0023270
Źródła finansowania:
  • COST_FREE
Weryfikacja:
Politechnika Gdańska

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