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1.
说话人识别是当前语音识别的研究热点之一。本文主要研究了以下几个方面:说话人语音识别系统,对能够反映人对语音感知特性的Mel频率倒谱系数(MFCC)作为特征参数进行提取。同时,分析了概率神经网络PNN,概率神经网络是性能良好的分类神经网络。实验结果表明,概率神经网络PNN对训练的语音样本有着很高的分类准确率。  相似文献   

2.
本文通过实验对比,在语音识别的特征参数方面进行了有效的改进,创新内容是改善Mel频谱倒谱系数(MFCC),将12阶Mel频谱倒谱系数减为11阶,通过实验证明,改进后的参数有效提高了实验的识别率。实验主要采用删减特征分量的方法研究MFCC各阶参数对非特定人特定语音识别的贡献,并通过大量重复性实验得出验证,不同的参数选择对语音识别确实有不同的贡献,而且针对不同的语本模型,贡献也不同。  相似文献   

3.
徐春辉 《科技广场》2007,(5):208-210
通过分析语音特征参数的特点和说话人识别的基本方法,以线性预测倒谱系数为特征参数提取算法以及隐马尔可夫模型为建模算法,利用凌阳单片机作硬件平台,实现了声控锁的语音控制功能。实验结果表明,系统性能稳定,识别效果良好。  相似文献   

4.
文章介绍了语音识别的基本原理以及用DSK6713实现语音识别算法的一些原则和方法,阐述了语音识别在DSP上的实现技术。系统使用梅尔倒谱系数(MFCC)作为特征参数,采用算法相对简单以及计算量较小的动态时间弯折算法(DTW)实现语音参数的匹配。用MATLAB实现DTW算法的仿真,进而将语音识别技术应用到DSP上,实验结果表明对特定人、小词汇量和孤立词的语音识别效果比较好。  相似文献   

5.
一种基于改进的LPC参数倒谱分析的说话人识别方法   总被引:2,自引:0,他引:2  
王婧  朱黎 《大众科技》2008,(8):28-29
线性预测倒谱LPCC在说话人识别中已被广泛使用,文章以LPCC为基础进行Mel变换,得到新的特征参数LPMCC,一次作为说话人识别系统的特征参数,并在识别部分采用VQ和HMM相结合的方法进行建模和识别,实验证明该方法提高了系统的识别率。  相似文献   

6.
改进MFCC参数在非特定人语音识别中的研究   总被引:1,自引:0,他引:1  
随着信息时代的高速发展,人们越来越关注计算机的便携使用方式,以语音输入代替手动输入成为计算机未来发展的一个必然趋势.本文在MFCC特征参数的基础上,提出了一种改进MFCC特征参数--BMFCC特征参数,以提高原MFCC特征参数在语音识别时的识别率和运算速度.BMFCC特征参数在进行参数的提取时,分为特征分量加权、特征分量求差分、主成分分析三个步骤.仿真实验结果表明,本文提出的BMFCC特征参数在识别率和有运算速度上均优于MFCC特征参数,且更具鲁棒性.  相似文献   

7.
为了适应强噪声环境下的语音识别,进行了基于美尔倒谱系数特征及隐马尔可夫模型的识别算法研究,主要对提取语音信号的线性预测系数、端点检测、语音特征参数提取、语音算法识别流程等进行了初步研究,并进行了说话人识别系统的仿真验证。  相似文献   

8.
为了得到更具区分性的特征参数,采用改进的MFCC提取方法,即低方差性的多窗谱估计MFCC,并在其基础上引入了短时TEO能量和ΔMFCC动态特征参量组合特征进行说话人识别。由于直接将两者进行组合会造成维度过高,计算复杂度增加,为此提出了相关距离Fisher比来对特征参数进行加权和维度筛选,最后送入GMM-UBM分类器模型进行识别。实验表明,改进的混合特征参数相较于单一的特征参量,具备更好的识别能力,使得识别率有一定程度的提高。  相似文献   

9.
MFCC特征参数提取是语音识别设计中非常重要的环节,MFCC特征参数提取的实现及参数的精确度对于最终语音识别的准确度有着非常大的影响。对于MFCC特征参数的提取主要的方法是利用MATLAB软件来实现。利用Labview软件调用MATLAB程序可将两者的优点综合起来,提高软件的适用性。  相似文献   

10.
藏族的主要语种,基于其上的声纹识别技术具有重大的研究意义;而在声纹识别过程中,语音特征参数的选择和精确度直接影响了声纹识别的准确率。文章针对藏语声纹识别的需要,选取MFCC为特征参数,对藏语语音的特征提取进行了研究和实践。  相似文献   

11.
针对标准的BP神经网络对于声音信号识别率不高的问题,提出了一种用粒子群算法(PSO)优化BP神经网络的算法,建立了声音信号识别模型。PSO优化BP神经网络主要是用PSO来优化BP神经网络的初始权值和闽值,然后通过训练BP神经网络得到识别模型的最优解,优化后的神经网络具有误判率小、反应速度快等特点。在实验中把标准的BP神经网络和PSO优化后的BP神经网络用于八种异常声音的MFCC特征量和差分MFCC特征量识别,结果表明:在声音信号的识别系统中采用PSO优化BP神经网络的算法提高了系统的识别性能,达到了系统设计的目的。  相似文献   

12.
以VC++6.0为开发平台,实现一个基于隐马尔可夫模型(Hidden Markov Model,简称HMM)非特定人的安多藏语孤立词语音识别系统。对有声段语音进行MFCC参数的提取,对提取后的MFCC参数进行矢量量化后训练HMM模型,形成特征模板库,最后进行识别。根据安多藏语的特点,改进端点检测的方法,提高了孤立词语音信号检测的准确性,并进一步提高了识别率。  相似文献   

13.
Identifying perceived emotional content of music constitutes an important aspect of easy and efficient search, retrieval, and management of the media. One of the most promising use cases of music organization is an emotion-based playlist, where automatic music emotion recognition plays a significant role in providing emotion related information, which is otherwise, generally unavailable. Based on the importance of the auditory system in emotional recognition and processing, in this study, we propose a new cochleogram-based system for detecting the affective musical content. To effectively simulate the response of the human auditory periphery, the music audio signal is processed by a detailed biophysical cochlear model, thus obtaining an output that closely matches the characteristics of human hearing. In this proposed approach, based on the cochleogram images, which we construct directly from the response of the basilar membrane, a convolutional neural network (CNN) is used to extract the relevant music features. To validate the practical implications of the proposed approach with regard to its possible integration in different digital music libraries, an extensive study was conducted to evaluate the predictive performance of our approach in different aspects of music emotion recognition. The proposed approach was evaluated on publicly available 1000 songs database and the experimental results showed that it performed better in comparison with common musical features (such as tempo, mode, pitch, clarity, and perceptually motivated mel-frequency cepstral coefficients (MFCC)) as well as official ”MediaEval” challenge results on the same reference database. Our findings clearly show that the proposed approach can lead to better music emotion recognition performance and be used as part of a state-of-the-art music information retrieval system.  相似文献   

14.
bidirectional delta file is a novel concept, introduced in this paper, for a two way delta file. Previous work focuses on single way differential compression called forwards and backwards delta files. Here we suggest to efficiently combine them into a single file so that the combined file is smaller than the combination of the two individual ones. Given the bidirectional delta file of two files S and T and the original file S, one can decode it in order to produce T. The same bidirectional delta file is used together with the file T in order to reconstruct S. This paper presents two main strategies for producing an efficient bidirectional delta file in terms of the memory storage it requires; a quadratic time, optimal, dynamic programming algorithm, and a linear time, greedy algorithm. Although the dynamic programming algorithm often produces better results than the greedy algorithm, it is impractical for large files, and it is only used for theoretical comparisons. Experiments between the implemented algorithms and the traditional way of using both forwards and backwards delta files are presented, comparing their processing time and their compression performance. These experiments show memory storage savings of about 25% using this bidirectional delta approach as compared to the compressed delta file constructed using the traditional way, while preserving approximately the same processing time for decoding.  相似文献   

15.
信息隐藏是20世纪90年代逐步兴起的研究课题。语音信号的不特定的静音间隔使得它比较于音乐等其他音频信号缺少了很大的隐藏空间,而语音信号的信息隐藏在Internet和有线与无线电话信道又有着很好的应用前景。提出一种语音信号的信息隐藏算法,能够在MFCC参数中隐藏秘密消息,语音的短时能量具有的较强的稳定性,可以保证隐藏和提取时的帧的同步,使得对应的提取算法可以准确地从隐藏的语音中恢复出信息。本方法可以适用于Internet信道和局域网络或高速网络中的语音应用。  相似文献   

16.
利用神经网络设计语音信号增强处理系统,在无噪和含噪条件下,提取语音信号的MFCC系数,用于BP神经网络的训练和识别,最终达到语音信号消噪和提高可懂度的目的。自适应神经网络系统具有非线性映射和自学习能力,能够用于噪声信号的非线性建模。它不仅能够获取信号的最佳估计,并且能够克服信号处理中存在的不确定性。仿真结果表明,该自适应噪声抵消器的设计方法,不仅实现简单,而且节省运行时间,语音增强效果很好。  相似文献   

17.
In this paper, a parametric delta operator Riccati equation is established for low gain feedbacks of linear delta operator systems. Some properties for the parametric delta operator Riccati equation are given based on a parameter-dependent cost function. An explicit solution is also given for the delta operator parametric Riccati equation. Semi-global stabilization is described for a linear delta operator system with actuator saturation via low gain state and output feedback control laws. A numerical example is given to illustrate the effectiveness and potential for the developed techniques.  相似文献   

18.
In this paper, an observer-based sliding mode control (SMC) problem is investigated for a class of uncertain delta operator systems with nonlinear exogenous disturbance. A novel robust stability condition is obtained for a sliding mode dynamics by using Lyapunov theory in delta domain. Based on a designed sliding mode observer, a sliding mode controller is synthesized by employing SMC theory combined with reaching law technique. The robust asymptotical stability problem is also discussed for the closed-loop system composed of the observer dynamics and the state estimation error dynamics. Furthermore, the reachability of sliding surfaces is also investigated in state-estimate space and estimation error space, respectively. Finally, a numerical example is given to illustrate the feasibility and effectiveness of the developed method.  相似文献   

19.
从城市集群的角度,定性分析长三角经济带开展科技创新合作的基础与优势,结合目前上海科技创新中心在长三角城市集群中所处的地位,制定上海借力长三角建设具有全球影响力科技创新中心的目标,提出依托长三角经济带推动上海科技创新中心建设的路径与对策。  相似文献   

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