B. Bhattacharya, W. LeBlanc, S. Mahmoud, V. Cuperman
{"title":"4 kb/s语音编码中LPC参数的树搜索多阶段矢量量化","authors":"B. Bhattacharya, W. LeBlanc, S. Mahmoud, V. Cuperman","doi":"10.1109/ICASSP.1992.225961","DOIUrl":null,"url":null,"abstract":"The authors present a tree searched multi-stage vector quantization (TS-MSVQ) scheme which achieves spectral distortion lower than 1 dB with low complexity and good robustness using 24 b/frame. The M-L search is used and it is shown that it achieves performance close to that of the optimal search for a relatively small M. The best performance/complexity trade-offs are obtained with relatively small size codebooks cascaded in a three-four stage configuration. Results for log-area ratio (LAR) and line spectral pain (LSP) parameters are presented. A training technique which reduces outliers at the expense of a slight average performance degradation is introduced. The robustness across different languages and input spectral shapings is studied. Finally, it is shown that TS-MSVQ significantly outperforms the split-codebook approach.<<ETX>>","PeriodicalId":163713,"journal":{"name":"[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing","volume":"107 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"31","resultStr":"{\"title\":\"Tree searched multi-stage vector quantization of LPC parameters for 4 kb/s speech coding\",\"authors\":\"B. Bhattacharya, W. LeBlanc, S. Mahmoud, V. Cuperman\",\"doi\":\"10.1109/ICASSP.1992.225961\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The authors present a tree searched multi-stage vector quantization (TS-MSVQ) scheme which achieves spectral distortion lower than 1 dB with low complexity and good robustness using 24 b/frame. The M-L search is used and it is shown that it achieves performance close to that of the optimal search for a relatively small M. The best performance/complexity trade-offs are obtained with relatively small size codebooks cascaded in a three-four stage configuration. Results for log-area ratio (LAR) and line spectral pain (LSP) parameters are presented. A training technique which reduces outliers at the expense of a slight average performance degradation is introduced. The robustness across different languages and input spectral shapings is studied. Finally, it is shown that TS-MSVQ significantly outperforms the split-codebook approach.<<ETX>>\",\"PeriodicalId\":163713,\"journal\":{\"name\":\"[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing\",\"volume\":\"107 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-03-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"31\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASSP.1992.225961\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.1992.225961","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Tree searched multi-stage vector quantization of LPC parameters for 4 kb/s speech coding
The authors present a tree searched multi-stage vector quantization (TS-MSVQ) scheme which achieves spectral distortion lower than 1 dB with low complexity and good robustness using 24 b/frame. The M-L search is used and it is shown that it achieves performance close to that of the optimal search for a relatively small M. The best performance/complexity trade-offs are obtained with relatively small size codebooks cascaded in a three-four stage configuration. Results for log-area ratio (LAR) and line spectral pain (LSP) parameters are presented. A training technique which reduces outliers at the expense of a slight average performance degradation is introduced. The robustness across different languages and input spectral shapings is studied. Finally, it is shown that TS-MSVQ significantly outperforms the split-codebook approach.<>