M. M. Rahaman, Anindya Das, M. Z. Nayen, Md. Saidur Rahman
{"title":"孟加拉语语音特征提取技术","authors":"M. M. Rahaman, Anindya Das, M. Z. Nayen, Md. Saidur Rahman","doi":"10.1109/ICCITECHN.2010.5723839","DOIUrl":null,"url":null,"abstract":"This paper describes several feature extraction techniques, which will facilitate Automatic Speech Recognition (ASR) for Bangla speech. These techniques are applied on different sound-packets, which are essentially segments of Bangla speech. The key temporal regions in a sound-packet that contain vital information about the speech signal are identified. Some novel feature extraction methods are developed using the information contained within these key regions. It has been observed that a single feature cannot provide enough information to achieve successful automatic speech recognition; rather a combination of the features can be used effectively to increase the accuracy.","PeriodicalId":149135,"journal":{"name":"2010 13th International Conference on Computer and Information Technology (ICCIT)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Special feature extraction techniques for Bangla speech\",\"authors\":\"M. M. Rahaman, Anindya Das, M. Z. Nayen, Md. Saidur Rahman\",\"doi\":\"10.1109/ICCITECHN.2010.5723839\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes several feature extraction techniques, which will facilitate Automatic Speech Recognition (ASR) for Bangla speech. These techniques are applied on different sound-packets, which are essentially segments of Bangla speech. The key temporal regions in a sound-packet that contain vital information about the speech signal are identified. Some novel feature extraction methods are developed using the information contained within these key regions. It has been observed that a single feature cannot provide enough information to achieve successful automatic speech recognition; rather a combination of the features can be used effectively to increase the accuracy.\",\"PeriodicalId\":149135,\"journal\":{\"name\":\"2010 13th International Conference on Computer and Information Technology (ICCIT)\",\"volume\":\"79 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 13th International Conference on Computer and Information Technology (ICCIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCITECHN.2010.5723839\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 13th International Conference on Computer and Information Technology (ICCIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCITECHN.2010.5723839","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Special feature extraction techniques for Bangla speech
This paper describes several feature extraction techniques, which will facilitate Automatic Speech Recognition (ASR) for Bangla speech. These techniques are applied on different sound-packets, which are essentially segments of Bangla speech. The key temporal regions in a sound-packet that contain vital information about the speech signal are identified. Some novel feature extraction methods are developed using the information contained within these key regions. It has been observed that a single feature cannot provide enough information to achieve successful automatic speech recognition; rather a combination of the features can be used effectively to increase the accuracy.