手势语言识别的神经网络方法

提供了一种用于人机交互（HCI）的手势语言可视化识别方法。该方法包括用于几种控制命令的手势的探测、分割、特征提取及识别，第一步的处理都用到了神经网络方法，像肤色探测、主元分析（PCA）以及在编码识别。实验结果显示正确识别率高达94％。     

A new speaker verification method with global speaker model and likelihood score normalization

In this paper a new text-independent speaker verification method GSMSV is proposed based on likelihood score normalization.In this novel method a global speaker model is established to represent the universal features of speech and normalize the likelihood score.Statistical analysis demonstrates that this normalization method can remove common factors of speech and bring the differences between speakers into prominence.As a result the equal error rate is decreased significantly,verification procedure is accelerated and system adaptability to speaking speed is improved.     

A Dialectal Chinese Speech Recognition Framework

A framework for dialectal Chinese speech recognition is proposed and studied, in which a relatively small dialectal Chinese (or in other words Chinese influenced by the native dialect) speech corpus and dialect-related knowledge are adopted to transform a standard Chinese (or Putonghua, abbreviated as PTH) speech recognizer into a dialectal Chinese speech recognizer. Two kinds of knowledge sources are explored: one is expert knowledge and the other is a small dialectal Chinese corpus. These knowledge sources provide information at four levels: phonetic level, lexicon level, language level, and acoustic decoder level. This paper takes Wu dialectal Chinese (WDC) as an example target language. The goal is to establish a WDC speech recognizer from an existing PTH speech recognizer based on the Initial-Final structure of the Chinese language and a study of how dialectal Chinese speakers speak Putonghua. The authors propose to use context-independent PTH-IF mappings (where IF means either a Chinese Initial or a Chinese Final), context-independent WDC-IF mappings, and syllable-dependent WDC-IF mappings (obtained from either experts or data), and combine them with the supervised maximum likelihood linear regression (MLLR) acoustic model adaptation method. To reduce the size of the multi-pronunciation lexicon introduced by the IF mappings, which might also enlarge the lexicon confusion and hence lead to the performance degradation, a Multi-Pronunciation Expansion (MPE) method based on the accumulated uni-gram probability (AUP) is proposed. In addition, some commonly used WDC words are selected and added to the lexicon. Compared with the original PTH speech recognizer, the resulting WDC speech recognizer achieves 10-18% absolute Character Error Rate (CER) reduction when recognizing WDC, with only a 0.62% CER increase when recognizing PTH. The proposed framework and methods are expected to work not only for Wu dialectal Chinese but also for other dialectal Chinese languages and even other languages.     

酷软与插件

为网页设计添“色”加瓦,自动化语言识别专家Polyglot,神奇的3D设计专家Phun,自定义系统启动程序,桌面更新随心所欲,瞬间音频视频提取工具,批量为数码照片添加日期,一秒搞定网速测试,将图片转换为文字画面,QQ相册随意下载,文件加密有奇招,     

连续语音识别中句法结构知识的利用

本文论述连续语音识别中如何利用句法结构知识。首先介绍句法结构模型的建立,然后阐述如何基于句法结构模型分析,从语音处理的初步结果搜索出输入语句的方法。本文提出了三种启发式搜索策略:(1)最大似然优先搜索(MLF);(2)局部最大似然优先(PMLF);(3)最大似然近邻法(MLNN)。     

让我说给你听——IBM ViaVoice亲身体验

IBM公司自1970年开始建立了二三十人组成的专门研究机构,迄今,已经成功地研制出多达8种语言的识别软件。IBM的汉语语音识别系统ViaVoice基本上是基于二十几年来IBM在英语语音识别领域的研究成果。是IBM公司针对汉字输入的特点推出的语音识别系统,它可支持中文Windows 95/98/NT平台,其语音识别的速度和准确率在同类产品中均处于领先地位。目前在北美,ViaVoice语言识别软件也已拥有超过600万的用户。 除了PC平台,1999年6月,IBM宣     

用PERL编程对自然语言（英语）的识别与分析

欧美国家医学部门如何自动识别门诊病历中的医学语，是自然语言（英语）识别的一项重要题。作者使用了Perl语言编程，并采用标准医学术语（Medical Concepts and Terms)数据库MRCON为样本数据库，并对MRCON进行了字段删减、库记录倒置和采用剔除查找时产生的冗余记录的算法等等，经对多例门诊诊断和放射线报告进行了识别和分析处理，取得了较高的关键词识别准确率和低冗余度，同时也为用Perl语言分析处理自然语言（NLP）探索了一条新的道路。     

语音识别技术在汽车上的应用

本文介绍了汽车应用语音识别技术的现状和问题。     

能识别语言的光学神经网络

能识别语言的光学神经网络光折变延时神经网络系统可望革新普通语言识别算法所需的计算任务。科罗拉多大学实验天体物理联合研究所已制作一种以全息延迟线和能区分时间相关信号团的体存储介质为基础的光折变系统。至今该系统已被训练来识别三种数字化口语——即“声音”、...