U. Bhaskar, S. Nandkumar, K. Swaminathan, G. Zakaria
{"title":"Quantization of SEW and REW components for 3.6 kbit/s coding based on PWI","authors":"U. Bhaskar, S. Nandkumar, K. Swaminathan, G. Zakaria","doi":"10.1109/SCFT.1999.781497","DOIUrl":null,"url":null,"abstract":"The design of a prototype waveform interpolation (PWI) based codec, operating at 3.6 kbit/s, is presented with main focus on the quantization of the slowly evolving waveform (SEW) and rapidly evolving waveform (REW) components. The SEW magnitude component is quantized using a hierarchical mean-shape-gain predictive vector quantization approach. SEW phase is derived using a phase model, based on a measure of voice periodicity. The REW magnitude is quantized using a gain and a sub-band based shape. The REW phase is obtained by high pass filtering a weighted combination of the SEW and a white noise process.","PeriodicalId":372569,"journal":{"name":"1999 IEEE Workshop on Speech Coding Proceedings. Model, Coders, and Error Criteria (Cat. No.99EX351)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"1999 IEEE Workshop on Speech Coding Proceedings. Model, Coders, and Error Criteria (Cat. No.99EX351)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SCFT.1999.781497","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
The design of a prototype waveform interpolation (PWI) based codec, operating at 3.6 kbit/s, is presented with main focus on the quantization of the slowly evolving waveform (SEW) and rapidly evolving waveform (REW) components. The SEW magnitude component is quantized using a hierarchical mean-shape-gain predictive vector quantization approach. SEW phase is derived using a phase model, based on a measure of voice periodicity. The REW magnitude is quantized using a gain and a sub-band based shape. The REW phase is obtained by high pass filtering a weighted combination of the SEW and a white noise process.