End-to-end Conversion Speed Analysis of an FPT.AI-based Text-to-Speech Application

In this paper, an FPT.AI-based text-to-speech (TTS) application is developed that converts Vietnamese text into spoken words. The application is developed based on Django for Python and in the form of an interactive web page which is connected to an FPT.AI server through its application programming...

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Main Authors: Chung, T.D., Drieberg, M., Bin Hassan, M.F., Khalyasmaa, A.
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.24638 /
Published: Institute of Electrical and Electronics Engineers Inc. 2020
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085167676&doi=10.1109%2fLifeTech48969.2020.1570620448&partnerID=40&md5=69ffc5e130e473e9d8519397ab61a341
http://eprints.utp.edu.my/24638/
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id utp-eprints.24638
recordtype eprints
spelling utp-eprints.246382021-08-27T06:13:27Z End-to-end Conversion Speed Analysis of an FPT.AI-based Text-to-Speech Application Chung, T.D. Drieberg, M. Bin Hassan, M.F. Khalyasmaa, A. In this paper, an FPT.AI-based text-to-speech (TTS) application is developed that converts Vietnamese text into spoken words. The application is developed based on Django for Python and in the form of an interactive web page which is connected to an FPT.AI server through its application programming interface (API). The application supports conversion of text to seven different Vietnamese speeches. Four out of seven voices can be used to convert up to 500 characters in a single transaction while the others support that of 400 characters. Based on the results obtained, the first conversion time takes up to 10 s to convert 400-character text into speech while the subsequent times, given same text, it takes under 1.8 s for the conversion. This is applicable to all voices. © 2020 IEEE. Institute of Electrical and Electronics Engineers Inc. 2020 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085167676&doi=10.1109%2fLifeTech48969.2020.1570620448&partnerID=40&md5=69ffc5e130e473e9d8519397ab61a341 Chung, T.D. and Drieberg, M. and Bin Hassan, M.F. and Khalyasmaa, A. (2020) End-to-end Conversion Speed Analysis of an FPT.AI-based Text-to-Speech Application. In: UNSPECIFIED. http://eprints.utp.edu.my/24638/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description In this paper, an FPT.AI-based text-to-speech (TTS) application is developed that converts Vietnamese text into spoken words. The application is developed based on Django for Python and in the form of an interactive web page which is connected to an FPT.AI server through its application programming interface (API). The application supports conversion of text to seven different Vietnamese speeches. Four out of seven voices can be used to convert up to 500 characters in a single transaction while the others support that of 400 characters. Based on the results obtained, the first conversion time takes up to 10 s to convert 400-character text into speech while the subsequent times, given same text, it takes under 1.8 s for the conversion. This is applicable to all voices. © 2020 IEEE.
format Conference or Workshop Item
author Chung, T.D.
Drieberg, M.
Bin Hassan, M.F.
Khalyasmaa, A.
spellingShingle Chung, T.D.
Drieberg, M.
Bin Hassan, M.F.
Khalyasmaa, A.
End-to-end Conversion Speed Analysis of an FPT.AI-based Text-to-Speech Application
author_sort Chung, T.D.
title End-to-end Conversion Speed Analysis of an FPT.AI-based Text-to-Speech Application
title_short End-to-end Conversion Speed Analysis of an FPT.AI-based Text-to-Speech Application
title_full End-to-end Conversion Speed Analysis of an FPT.AI-based Text-to-Speech Application
title_fullStr End-to-end Conversion Speed Analysis of an FPT.AI-based Text-to-Speech Application
title_full_unstemmed End-to-end Conversion Speed Analysis of an FPT.AI-based Text-to-Speech Application
title_sort end-to-end conversion speed analysis of an fpt.ai-based text-to-speech application
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2020
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085167676&doi=10.1109%2fLifeTech48969.2020.1570620448&partnerID=40&md5=69ffc5e130e473e9d8519397ab61a341
http://eprints.utp.edu.my/24638/
_version_ 1741196844981026816
score 11.62408

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