检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

5 篇 会议

馆藏范围

5 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

5 篇 工学
- 3 篇 计算机科学与技术...
- 2 篇 电气工程
- 2 篇 信息与通信工程
- 1 篇 控制科学与工程
2 篇 理学
- 2 篇 物理学

主题

5 篇 deterministic an...
2 篇 hidden markov mo...
2 篇 hidden markov mo...
2 篇 eigenvoice
2 篇 face recognition
2 篇 separable lattic...
2 篇 hmm-based speech...
2 篇 factor analysis
2 篇 expectation maxi...
1 篇 mixtures of prob...
1 篇 rotational
1 篇 speech
1 篇 sequential monte...
1 篇 decision trees
1 篇 facial recogniti...
1 篇 expectation-maxi...
1 篇 speech synthesis
1 篇 image recognitio...
1 篇 voice
1 篇 motion capture

机构

2 篇 nagoya inst tech...
2 篇 nagoya institute...
1 篇 univ tokyo grad ...

作者

2 篇 tokuda keiichi
2 篇 keiichi tokuda
2 篇 nankaku yoshihik...
2 篇 yoshihiko nankak...
1 篇 kyosuke kazumi
1 篇 mori t
1 篇 kazumi kyosuke
1 篇 tamamori akira
1 篇 harada t
1 篇 sato t
1 篇 akira tamamori

语言

5 篇 英文

检索条件"主题词=deterministic annealing EM algorithm"

共 5 条记录，以下是1-10 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

AN EXTENSION OF SEPARABLE LATTICE 2-D HMMS FOR ROTATIONAL DATA VARIATIONS

AN EXTENSION OF SEPARABLE LATTICE 2-D HMMS FOR ROTATIONAL DA...

引用

2010 IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Tamamori, Akira Nankaku, Yoshihiko Tokuda, Keiichi Nagoya Inst Technol Nagoya Aichi Japan

ISBN: (纸本)9781424442966

This paper proposes a new generative model which can deal with rotational data variations by extending Separable Lattice 2-D HMMs (SL2D-HMMs). In image recognition, geometrical variations such as size, location and rotation degrade the performance, therefore normalization is required. SL2D-HMMs can perform an elastic matching in both horizontal and vertical directions;this makes it possible to model invariances to size and location. To deal with rotational variations, we introduce additional HMM states which represent the shifts of the state alignments of the observation lines in a particular direction. Face recognition experiments show that the proposed method improves the performance significantly for rotational variation data.

关键词： Face recognition Hidden Markov model Separable lattice 2-D HMM deterministic annealing em algorithm

来源：评论

学校读者我要写书评

暂无评论

FACTOR ANALYZED VOICE MODELS FOR HMM-BASED SPEECH SYNTHESIS

FACTOR ANALYZED VOICE MODELS FOR HMM-BASED SPEECH SYNTHESIS

引用

2010 IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Kazumi, Kyosuke Nankaku, Yoshihiko Tokuda, Keiichi Nagoya Inst Technol Nagoya Aichi Japan

ISBN: (纸本)9781424442966

This paper describes factor analyzed voice models for realizing various voice characteristics in the HMM-based speech synthesis. The eigenvoice method can synthesize speech with arbitrary voice characteristics by interpolating representative HMM sets. However, the objective of PCA is to accurately reconstruct each speaker-dependent HMM set, and this is not equivalent to estimating models which represent training data accurately. To overcome this problem, we propose a general speech model which generates speech utterances with various voice characteristics directly. In the proposed method, the HMM states, factors representing voice characteristics and contextual decision trees are simultaneously optimized within a unified framework.

关键词： HMM-based speech synthesis eigenvoice factor analysis expectation maximization algorithm deterministic annealing em algorithm

来源：评论

学校读者我要写书评

暂无评论

Human posture reconstruction based on posture probability density

Human posture reconstruction based on posture probability de...

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Harada, T Sato, T Mori, T Univ Tokyo Grad Sch Informat Sci & Technol Tokyo 1138656 Japan

ISBN: (纸本)0780389123

In this paper, we propose a human posture reconstruction method from the insufficient input posture data based on human posture probability density that is constructed by a long-term human motion capture data. Since the long continuous daily human motion data has high dimensions and becomes huge size, the human posture data should be effectively compressed. The long term posture data has nonlinear distribution on the posture space, since each specific posture such as standing and sitting has different property. The posture data is allocated into some subspaces and compressed for each subspace with Mixtures of Probabilistic Principal Component Analyzer (MPPCA). MPPCA is improved by replacing conventional em algorithm with deterministic annealing em algorithm (DAem) to avoid initial parameter sensitivity. The posture probability density is constructed over those subspaces. The adequate human posture can be reconstructed from the insufficient data by introducing the posture probability density into the Sequential Monte Carlo frame work. The experimental results show that the robust human posture estimation can be realized since this method does not estimate the unique posture but estimates the proper posterior posture density with using the posture prior knowledge.

关键词： mixtures of Probabilistic Principal Component Analyzer sequential Monte Carlo deterministic annealing em algorithm motion capture

来源：评论

学校读者我要写书评

暂无评论

FACTOR ANALYZED VOICE MODELS FOR HMM-BASED SPEECH SYNTHESIS

FACTOR ANALYZED VOICE MODELS FOR HMM-BASED SPEECH SYNTHESIS

引用

IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Kyosuke Kazumi Yoshihiko Nankaku Keiichi Tokuda Nagoya Institute of Technology Nagoya Japan

ISBN: (纸本)9781424442959