{"title":"Telephony speech system performance based on the codec effect","authors":"Mohamed Hamidi, Ouissam Zealouk, Hassan Satori","doi":"10.1007/s12243-023-00968-5","DOIUrl":null,"url":null,"abstract":"<div><h2>Abstract\n</h2><div><p>This paper is a part of our contribution to research on the enhancement of network automatic speech recognition system performance. We built a highly configurable platform by using hidden Markov models, Gaussian mixture models, and Mel frequency spectral coefficients, in addition to VoIP G.711-u and GSM codecs. To determine the optimal values for maximum performance, different acoustic models are prepared by varying the hidden Markov models (from 3 to 5) and Gaussian mixture models (8–16-32) with 13 feature extraction coefficients. Additionally, our generated acoustic models are tested by unencoded and encoded speech data based on G.711 and GSM codecs. The best parameterization performance is obtained for 3 HMM, 8–16 GMMs, and G.711 codecs.</p></div></div>","PeriodicalId":50761,"journal":{"name":"Annals of Telecommunications","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Telecommunications","FirstCategoryId":"94","ListUrlMain":"https://link.springer.com/article/10.1007/s12243-023-00968-5","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract
This paper is a part of our contribution to research on the enhancement of network automatic speech recognition system performance. We built a highly configurable platform by using hidden Markov models, Gaussian mixture models, and Mel frequency spectral coefficients, in addition to VoIP G.711-u and GSM codecs. To determine the optimal values for maximum performance, different acoustic models are prepared by varying the hidden Markov models (from 3 to 5) and Gaussian mixture models (8–16-32) with 13 feature extraction coefficients. Additionally, our generated acoustic models are tested by unencoded and encoded speech data based on G.711 and GSM codecs. The best parameterization performance is obtained for 3 HMM, 8–16 GMMs, and G.711 codecs.
期刊介绍：
Annals of Telecommunications is an international journal publishing original peer-reviewed papers in the field of telecommunications. It covers all the essential branches of modern telecommunications, ranging from digital communications to communication networks and the internet, to software, protocols and services, uses and economics. This large spectrum of topics accounts for the rapid convergence through telecommunications of the underlying technologies in computers, communications, content management towards the emergence of the information and knowledge society. As a consequence, the Journal provides a medium for exchanging research results and technological achievements accomplished by the European and international scientific community from academia and industry.
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