{"title":"基于可重构并行处理器的语音识别HMM训练","authors":"HyunJeong Yun, Aaron Smith, H. Silverman","doi":"10.1109/FPGA.1997.624627","DOIUrl":null,"url":null,"abstract":"Armstrong III is a 20 node multi-computer that is currently operational. In addition to a RISC processor, each node contains reconfigurable resources implemented with FPGAs. The in-circuit reprogramability of static RAM based FPGAs allows the computational capabilities of a node to be dynamically matched to the computational requirements of an application. Most reconfigurable computers in existence today rely solely on a large number of FPGAs to perform computations. In contrast, the paper demonstrates the utility of a small number of FPGAs coupled to a RISC processor with a simple interconnect. The article describes a substantive example application that performs HMM training for speech recognition with the reconfigurable platform.","PeriodicalId":303064,"journal":{"name":"Proceedings. The 5th Annual IEEE Symposium on Field-Programmable Custom Computing Machines Cat. No.97TB100186)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":"{\"title\":\"Speech recognition HMM training on reconfigurable parallel processor\",\"authors\":\"HyunJeong Yun, Aaron Smith, H. Silverman\",\"doi\":\"10.1109/FPGA.1997.624627\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Armstrong III is a 20 node multi-computer that is currently operational. In addition to a RISC processor, each node contains reconfigurable resources implemented with FPGAs. The in-circuit reprogramability of static RAM based FPGAs allows the computational capabilities of a node to be dynamically matched to the computational requirements of an application. Most reconfigurable computers in existence today rely solely on a large number of FPGAs to perform computations. In contrast, the paper demonstrates the utility of a small number of FPGAs coupled to a RISC processor with a simple interconnect. The article describes a substantive example application that performs HMM training for speech recognition with the reconfigurable platform.\",\"PeriodicalId\":303064,\"journal\":{\"name\":\"Proceedings. The 5th Annual IEEE Symposium on Field-Programmable Custom Computing Machines Cat. No.97TB100186)\",\"volume\":\"37 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-04-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"13\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. The 5th Annual IEEE Symposium on Field-Programmable Custom Computing Machines Cat. No.97TB100186)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FPGA.1997.624627\",\"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. The 5th Annual IEEE Symposium on Field-Programmable Custom Computing Machines Cat. No.97TB100186)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FPGA.1997.624627","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Speech recognition HMM training on reconfigurable parallel processor
Armstrong III is a 20 node multi-computer that is currently operational. In addition to a RISC processor, each node contains reconfigurable resources implemented with FPGAs. The in-circuit reprogramability of static RAM based FPGAs allows the computational capabilities of a node to be dynamically matched to the computational requirements of an application. Most reconfigurable computers in existence today rely solely on a large number of FPGAs to perform computations. In contrast, the paper demonstrates the utility of a small number of FPGAs coupled to a RISC processor with a simple interconnect. The article describes a substantive example application that performs HMM training for speech recognition with the reconfigurable platform.