{"title":"基于遗传算法的二阶语音模型","authors":"L. Mitiche, A. Adamou-Mitiche","doi":"10.1109/CEIT.2016.7929077","DOIUrl":null,"url":null,"abstract":"Using a new model order reduction based on frequency selection and optimal genetic algorithm, a very low order speech model is presented. In our approach, the modeling process starts with a full-order classical all poles model obtained by some known methods. The original model is then reduced using a new proposed approach based on the genetic algorithms and the full order speech production system dominant frequencies. The model reduction yields to a zeros-poles reduced order model which interestingly preserves the key properties of the original full-order model in the time and frequency domains. To illustrate the performance and the effectiveness of the proposed approach, some computer simulations are conducted on some practical speech segments. To show the novelty of our approach, a comparative study with an approximant given by an appropriate conventional techniques is presented.","PeriodicalId":355001,"journal":{"name":"2016 4th International Conference on Control Engineering & Information Technology (CEIT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Second order speech model based on GA's\",\"authors\":\"L. Mitiche, A. Adamou-Mitiche\",\"doi\":\"10.1109/CEIT.2016.7929077\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Using a new model order reduction based on frequency selection and optimal genetic algorithm, a very low order speech model is presented. In our approach, the modeling process starts with a full-order classical all poles model obtained by some known methods. The original model is then reduced using a new proposed approach based on the genetic algorithms and the full order speech production system dominant frequencies. The model reduction yields to a zeros-poles reduced order model which interestingly preserves the key properties of the original full-order model in the time and frequency domains. To illustrate the performance and the effectiveness of the proposed approach, some computer simulations are conducted on some practical speech segments. To show the novelty of our approach, a comparative study with an approximant given by an appropriate conventional techniques is presented.\",\"PeriodicalId\":355001,\"journal\":{\"name\":\"2016 4th International Conference on Control Engineering & Information Technology (CEIT)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 4th International Conference on Control Engineering & Information Technology (CEIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CEIT.2016.7929077\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 4th International Conference on Control Engineering & Information Technology (CEIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEIT.2016.7929077","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using a new model order reduction based on frequency selection and optimal genetic algorithm, a very low order speech model is presented. In our approach, the modeling process starts with a full-order classical all poles model obtained by some known methods. The original model is then reduced using a new proposed approach based on the genetic algorithms and the full order speech production system dominant frequencies. The model reduction yields to a zeros-poles reduced order model which interestingly preserves the key properties of the original full-order model in the time and frequency domains. To illustrate the performance and the effectiveness of the proposed approach, some computer simulations are conducted on some practical speech segments. To show the novelty of our approach, a comparative study with an approximant given by an appropriate conventional techniques is presented.