{"title":"罗马尼亚语的元音识别","authors":"O. Grigore, I. Gavat, M. Zirra","doi":"10.1109/SMICND.1997.651330","DOIUrl":null,"url":null,"abstract":"In this paper are presented results obtained in a vowel recognition task applying unsupervised and supervised fuzzy algorithms and neural networks. The vowels, uttered from 10 speakers each in 250 different contexts are recognized using as features the first three formant frequencies. After an introduction, the feature extraction is presented and then the two fuzzy algorithms (fuzzy ISODATA, fuzzy k-NN) and the two neural nets (nonlinear perceptron, Kohonen map) used for recognition are given.","PeriodicalId":144314,"journal":{"name":"1997 International Semiconductor Conference 20th Edition. CAS '97 Proceedings","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Vowel recognition in Romanian language\",\"authors\":\"O. Grigore, I. Gavat, M. Zirra\",\"doi\":\"10.1109/SMICND.1997.651330\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper are presented results obtained in a vowel recognition task applying unsupervised and supervised fuzzy algorithms and neural networks. The vowels, uttered from 10 speakers each in 250 different contexts are recognized using as features the first three formant frequencies. After an introduction, the feature extraction is presented and then the two fuzzy algorithms (fuzzy ISODATA, fuzzy k-NN) and the two neural nets (nonlinear perceptron, Kohonen map) used for recognition are given.\",\"PeriodicalId\":144314,\"journal\":{\"name\":\"1997 International Semiconductor Conference 20th Edition. CAS '97 Proceedings\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-10-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1997 International Semiconductor Conference 20th Edition. CAS '97 Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SMICND.1997.651330\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1997 International Semiconductor Conference 20th Edition. CAS '97 Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMICND.1997.651330","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper are presented results obtained in a vowel recognition task applying unsupervised and supervised fuzzy algorithms and neural networks. The vowels, uttered from 10 speakers each in 250 different contexts are recognized using as features the first three formant frequencies. After an introduction, the feature extraction is presented and then the two fuzzy algorithms (fuzzy ISODATA, fuzzy k-NN) and the two neural nets (nonlinear perceptron, Kohonen map) used for recognition are given.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
