@inproceedings{scholars13388, pages = {136--139}, title = {End-to-end Conversion Speed Analysis of an FPT.AI-based Text-to-Speech Application}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, journal = {LifeTech 2020 - 2020 IEEE 2nd Global Conference on Life Sciences and Technologies}, doi = {10.1109/LifeTech48969.2020.1570620448}, year = {2020}, note = {cited By 11; Conference of 2nd IEEE Global Conference on Life Sciences and Technologies, LifeTech 2020 ; Conference Date: 10 March 2020 Through 12 March 2020; Conference Code:159607}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085167676&doi=10.1109\%2fLifeTech48969.2020.1570620448&partnerID=40&md5=69ffc5e130e473e9d8519397ab61a341}, keywords = {Websites, Conversion speed; Conversion time; End to end; ITS applications; Spoken words; Text to speech; Vietnamese; Vietnamese speech, Application programming interfaces (API)}, abstract = {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. {\^A}{\copyright} 2020 IEEE.}, author = {Chung, T. D. and Drieberg, M. and Bin Hassan, M. F. and Khalyasmaa, A.}, isbn = {9781728170633} }