说话人识别技术在智能家居中的应用

结合智能型楼宇控制系统的特点以及以人为本的理念,提出了一种用DSP实现的说话人识别实时系统．并结合楼宇自动控制网络(BACnet)协议,将系统设计为BACnet设备的一个嵌入式子系统,从而将语音识别技术应用到智能家居控制系统中。     

语音识别技术在BACnet网络中的应用

在介绍语音识别和BACnet的基本知识的基础上，着重阐述了将语音识别技术应用于BACnet之中。提出了两种语音识别技术用于BACnet的方案。即把对说话人的确认作为操作员密码和识别操作员的口述命令。     

用反馈式语音识别理解方案进行汉语短语的识别理解

汉语语音理解系统的任务之一是把语音识别系统获得的汉语单单节转换成正确的汉字，词乃至汉语的短语，语句，与误音识别系统一起，完成一个语音到文本（ｓｐｅｅｃｈｔｏｔｅｘｔ）的转换系统，本文利用一个闭环反馈方式汉语语音识别理解方案，在汉语词识别理解的基础上，进一步实现时汉语结构性短的识别理解，获得了预期的结果，最后本文对实验结果和反馈式语音识别理解方案进行了讨论。     

基于STM32单片机控制的智能语音刷卡系统设计

阐述STM32单片机控制的智能语音刷卡系统中的内部结构、语音识别功能,智能语音刷卡系统的功能模块,包括中央控制系统、语音识别模块、电平串口模块、蓝牙模块、显示模块、刷卡模块、供电模块,探讨智能语音刷卡系统的程序设计。     

基于多口音语音识别的老人卧室智能家居控制系统设计

针对传统智能家居控制系统中无法对老年人的多口音语音进行准确识别的弊端,设计一种基于多口音语音识别的老人卧室智能家居控制系统,通过对WSN电路、特定老人多口音语音识别芯片以及MCU等硬件和老人语音指令的接收、处理和输出三个模块的软件设计,实现老年人对智能家居的基本需求.通过对比实验验证该系统的控制正确率明显高于传统控制系统,从而进一步加深对智能家居的控制.     

基于BACnet/IP协议智能楼宇网关系统功能设计

分析了传统楼宇自控系统的不足之处以及对智能化集中式楼宇自控系统的需求,并详细阐述了文章设计的智能楼宇网关系统的功能需求和系统设计的方案。本智能楼宇网关系统基于Web服务技术架构,主要实现BACnet协议栈解析、自动轮询推送、远程在线配置、BACnet对象读写以及日志管理、异常管理等功能。     

英语口语自动发音校对系统设计

针对传统的英语发音自动校对系统中语音识别混乱的问题,设计一种英语口语自动发音校对系统。引进灭错计算进行语音的识别校对,通过灭错计算的语音信息能够进行高阶识别,避免传统的识别校对方法中出现的数据进阶误差,同时优化了反馈控制系统,提高系统的识别语音的能力。为了验证所设计的英语口语自动发音校对系统的有效性,设计了对比仿真试验。试验数据表明,设计的英语口语自动发音校对系统能够有效地解决语音识别混乱问题。     

BACnet协议在照明控制系统中的应用

在详细分析BACnet协议和照明控制系统特点的基础上,将BACnet协议应用在照明控制系统中,给出了一种利用BACnet协议实现照明集中控制的方法。     

基于语音识别技术和蓝牙技术的数字化家庭综合设计

语音识别技术是让机器通过识别和理解过程把语音信号转变为相应的文本或命令，其识别过程与人对语音识别处理过程基本上是一致的，包括语音特征提取、声学模型与模式匹配（识别算法）、语言模型与语言处理三个部分。     

用反馈式语音识别理解方案进行汉语地名的识别理解

汉语语音理解系统的任务之一是把语音识别系统获得的汉语音节转换成正确的汉字，与汉语语音识别系统一起，完成一个语音-文本（SpeechtoText）的转换系统。本文利用一个有别于语音理解传统方法（1．语言学方法[1]，2．统计学方法[2])的新的反馈式语音理解方案进行汉语地名的识别理解，获得了很好的实验结果。本文最后对实验结果和反馈式语音识别理解方案进行了讨论。     

A statistical causal model for the assessment of dysarthric speechand the utility of computer-based speech recognition

The evaluation of the degree of speech impairment and the utility of computer recognition of impaired speech are separately and independently performed. Particular attention is paid to the question concerning whether or not there is a relationship between naive listeners' subjective judgments of impaired speech and the performance of a laboratory version of a speech recognition system. It is a difficult task to relate a speech impairment rating with speech recognition accuracy. Towards this end, a statistical causal model is proposed. This model is very appealing in its structure to support inference, and thus can be applied to perform various assessments such as the success of automatic recognition of dysarthric speech. The application of this model is illustrated with a case study of a dysarthric speaker compared against a normal speaker serving as a control     

嵌入式语音控制选单系统的实现与应用

采用ARM处理器$3C2440A构建嵌入式系统，利用音频芯片UDA1341TS对语音信号进行编解码，应用语音识别技术实现语音控制。介绍了系统设计原理和工作机制，并阐述了控制选单的软硬件设计方案和识别算法原理，给出测试方法。实验结果表明，系统能实现特定指令的语音控制，识别率高、实时性好，可适应复杂的工作环境。     

Application of Emotion Recognition and Modification for Emotional Telugu Speech Recognition

Majority of the automatic speech recognition systems (ASR) are trained with neutral speech and the performance of these systems are affected due to the presence of emotional content in the speech. The recognition of these emotions in human speech is considered to be the crucial aspect of human-machine interaction. The combined spectral and differenced prosody features are considered for the task of the emotion recognition in the first stage. The task of emotion recognition does not serve the sole purpose of improvement in the performance of an ASR system. Based on the recognized emotions from the input speech, the corresponding adapted emotive ASR model is selected for the evaluation in the second stage. This adapted emotive ASR model is built using the existing neutral and synthetically generated emotive speech using prosody modification method. In this work, the importance of emotion recognition block at the front-end along with the emotive speech adaptation to the ASR system models were studied. The speech samples from IIIT-H Telugu speech corpus were considered for building the large vocabulary ASR systems. The emotional speech samples from IITKGP-SESC Telugu corpus were used for the evaluation. The adapted emotive speech models have yielded better performance over the existing neutral speech models.

     

具有语音辨识能力的声控汽车的实现

采用Sunplus 16位MCU中的SPCE061A作为硬件平台，实现应用语音识别来控制玩具车。主要研究了如何将语音识别用于控制领域，进而给出使用SPCE061A的语音识别与控制功能的方法和技巧。     

Automatic context induction for tone model integration in mandarin speech recognition

Tone model (TM) integration is an important task for mandarin speech recognition.It has been proved to be effective to use discriminatively trained scaling factors when integrating TM scores into multi...     

基于Viseme的连续语音识别系统及Talking Head

为实现听觉/视觉驱动的说话人头部动画,该文给出了一个基于viseme(说话时的基本嘴形单位)的连续语音识别系统。它训练viseme隐马尔可夫模型(HMM),识别语音为viseme图像序列。建模采用triseme的概念来考虑viseme的上下文相关性,但它需要超大量的训练数据。该文根据viseme图像及其相似度权值(VSW)定义视觉问题集,用来建立triseme决策树,以实现triseme的状态捆绑及HMM参数共享。为比较系统性能,基于phoneme(听觉领域的语音基本单位)的语音识别结果也被映射为viseme序列。在评价准则上,定义viseme图像相似度加权识别精度,更全面地考虑输出和参考图像序列的差别,并用嘴形圆度和VSW曲线中的突变点来评估所得viseme序列的平滑性。结果表明,基于viseme的语音识别系统能给出更平滑和合理的嘴形图像序列。     

Smart buildings

Can building automation systems overcome interoperability problems to assert control over our offices, hotels, and airports? Efforts to make buildings smarter are focusing on cutting costs by streamlining building operations like air conditioning and lighting. Building automation is critical to these efforts, mainly because it could reduce the annual operating costs of buildings. This article outlines the latest building automation systems including the BACnet and LonWorks that integrate the services.     

Use of Microphone Array and Model Adaptation for Hands-Free Speech Acquisition and Recognition

This paper presents a combined microphone array and model adaptation algorithm for hands-free speech recognition. Our purpose is to remove the inconvenience of using head-mounted/hand-holding microphone in conventional speech recognizer. To improve the speech quality with car noise interference, a linear microphone array is applied and acted as robust acquisition system. A time-domain coherence measure (TDCM) is applied to reliably estimate the time delay for speech signals collected by different microphones. The estimated delay is adopted in a delay-and-sum beamformer for speech enhancement. Further, we adapt the speech hidden Markov models to get close to the acoustic conditions of the enhanced test speech for robust speech recognition. In acquisition and recognition experiments using connected Chinese digits, we found that TDCM can effectively estimate the time delay. The increase in the speech sampling rate is helpful to determine the time delay. Incorporating the model adaptation scheme significantly reduces the recognition errors with moderate computation overhead.     

基于AVR单片机的语音识别系统设计

系统以AVR单片机为控制核心,实现对人的语音的识别控制。系统采用的主控芯片为Atmel公司的ATMEGA128,语音识别功能采用ICRoute公司的单芯片LD3320。LD3320内部集成语音识别算法,无需外部FLASH,RAM资源,可以很好地完成非特定人的语音识别任务。同时该芯片内部集成了MP3播放功能,支持MPEG等格式,可实现语音提示或MP3歌曲的播放功能。由于内部合有16位A／D、D／A转换器和功放电路,所以不需要外接功放电路就可以产生清晰的声音。该系统已经预留好各种接口,具有良好的扩展性。