{"title":"基于音节合成算法的文本到语音合成器的设计与实现,并与发音合成算法进行了比较","authors":"E. Alexandra, P. Bharathi","doi":"10.1109/ICBATS54253.2022.9759063","DOIUrl":null,"url":null,"abstract":"Aim: The aim of the study is to design and implement a Text to speech Synthesizer based on syllabification synthesis algorithm and articulator synthesis algorithm to reduce computational time and to increase effectiveness in speech intelligibility. Materials and methods: The Text Datasets was used to implement the algorithm and sample for 10 different Text databases having different numbers of words.The input text Datasets will be ranging from 50-500 words. Results: The Statistical analysis was calculated and done by performing Independent Variable test and T-test and the obtained significance is 0.039 (p<0.05). The mean computational time of proposed algorithm 90% and the existing algorithm which is 78%. Conclusion: The algorithm based on the Syllabification algorithm shows higher computational time and lesser effectiveness in speech intelligence than the innovative algorithm based on Articulator speech synthesis.","PeriodicalId":289224,"journal":{"name":"2022 International Conference on Business Analytics for Technology and Security (ICBATS)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Design and Implementation of Text to speech synthesizer using Syllabification synthesis algorithm and comparing with Articulator Synthesis algorithm\",\"authors\":\"E. Alexandra, P. Bharathi\",\"doi\":\"10.1109/ICBATS54253.2022.9759063\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aim: The aim of the study is to design and implement a Text to speech Synthesizer based on syllabification synthesis algorithm and articulator synthesis algorithm to reduce computational time and to increase effectiveness in speech intelligibility. Materials and methods: The Text Datasets was used to implement the algorithm and sample for 10 different Text databases having different numbers of words.The input text Datasets will be ranging from 50-500 words. Results: The Statistical analysis was calculated and done by performing Independent Variable test and T-test and the obtained significance is 0.039 (p<0.05). The mean computational time of proposed algorithm 90% and the existing algorithm which is 78%. Conclusion: The algorithm based on the Syllabification algorithm shows higher computational time and lesser effectiveness in speech intelligence than the innovative algorithm based on Articulator speech synthesis.\",\"PeriodicalId\":289224,\"journal\":{\"name\":\"2022 International Conference on Business Analytics for Technology and Security (ICBATS)\",\"volume\":\"106 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-02-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Business Analytics for Technology and Security (ICBATS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICBATS54253.2022.9759063\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Business Analytics for Technology and Security (ICBATS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBATS54253.2022.9759063","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design and Implementation of Text to speech synthesizer using Syllabification synthesis algorithm and comparing with Articulator Synthesis algorithm
Aim: The aim of the study is to design and implement a Text to speech Synthesizer based on syllabification synthesis algorithm and articulator synthesis algorithm to reduce computational time and to increase effectiveness in speech intelligibility. Materials and methods: The Text Datasets was used to implement the algorithm and sample for 10 different Text databases having different numbers of words.The input text Datasets will be ranging from 50-500 words. Results: The Statistical analysis was calculated and done by performing Independent Variable test and T-test and the obtained significance is 0.039 (p<0.05). The mean computational time of proposed algorithm 90% and the existing algorithm which is 78%. Conclusion: The algorithm based on the Syllabification algorithm shows higher computational time and lesser effectiveness in speech intelligence than the innovative algorithm based on Articulator speech synthesis.