轿车ASR的ADAMS_CAR和MATLAB联合仿真,很详细
2019-12-21 21:23:18 1.46MB 联合仿真
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Kaldi单音素GMM学习笔记。从原理、脚本、程序和类四个方面介绍单音素GMM和Kaldi代码。Kaldi单音素GMM学习笔记。从原理、脚本、程序和类四个方面介绍单音素GMM和Kaldi代码。Kaldi单音素GMM学习笔记。从原理、脚本、程序和类四个方面介绍单音素GMM和Kaldi代码。
2019-12-21 21:20:26 785KB kaldi ASR GMM 单音素
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cisco asr 9000 系列产品手册
2019-12-21 21:06:39 4.65MB cisco 配置
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千里之行购物网站实现技术java+javaScript+Html+sqlServer2005 前台功能:客户购物、查询商品等 后台功能:管理商品、管理用户等
2019-12-21 21:02:43 2.97MB java javaSrcript javaWeb 源代码
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全 新的 ASR6501 SiP 使用了超小 6 平方毫米封装规格,集成了赛普拉斯 PSoC 4100S Plus MCU 以及 Semtech 公司的 LoRa 收发器,包含ASR6501官方DataSheet,原理图,BOM清单
2019-12-21 20:31:36 34.51MB ASR6501 LoRa
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拼音汉字对照表,格式已整理好,可直接应用于自然语言处理。(经过实践检验可以使用)
2019-12-21 20:16:47 24KB ASR 自然语言处理 拼音汉字对照
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Automatic Speech Recognition| ASR Lecture. About 18 lectures, plus a couple of extra lectures on basic introduction to neural networks. Lecturers: Steve Renals and Hiroshi Shimodaira.
2019-12-21 20:12:35 14.26MB asr 语音识别 ai kaldi
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数据库的书数据库的书数据库的书数据库的书数据库的书数据库的书数据库的书数据库的书数据库的书
2019-12-21 19:52:12 5.49MB Fundamentals of Database
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Hidden Markov Models (HMMs) provide a simple and effective framework for modelling time-varying spectral vector sequences. As a consequence, almost all present day large vocabulary continuous speech recognition (LVCSR) systems are based on HMMs. Whereas the basic principles underlying HMM-based LVCSR are rather straightforward, the approximations and simplifying assumptions involved in a direct implementation of these principles would result in a system which has poor accuracy and unacceptable sensitivity to changes in operating environment. Thus, the practical application of HMMs in modern systems involves considerable sophistication. The aim of this review is first to present the core architecture of a HMM-based LVCSR system and then describe the various refinements which are needed to achieve state-of-the-art performance. These refinements include feature projection, improved covariance modelling, discriminative parameter estimation, adaptation and normalisation, noise compensation and multi-pass system combination. The review concludes with a case study of LVCSR for Broadcast News and Conversation transcription in order to illustrate the techniques described.
2019-12-21 18:51:31 617KB HMM ASR AI
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