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基于ARM7TDMI的SoC片内AC97模块和片外CODEC-UCB1400，采用ITU-T的G.721算法设计语音处理系统 提出一种基于低端RISC核的语音系统设计方案。该方案结合SoC的片内eSRAM模块进行性能优化；通过在流片后的实际样机上验证，编码速率为19.88 KB/s，解码速率为22.68 KB/s，达到了语音实时性要求。-ARM7TDMI-based SoC chip AC97 module and off-chip CODEC-mated 00. using the ITU-T
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This scr ipt runs a simulation loop for either a linear or a DFE equalizer. It
uses the RLS algorithm to initially set the weights, then uses LMS thereafter to minimize execution time. It plots the equalized signal spectrum, then generates and plot
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A paper that I presented on Supervisory Control and Data Acquisition (SCADA) won the second prize at the symposium conducted by the Electrical and Electronics Engineering department of the SRM University. Other topics on which I presented papers were
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A paper that I presented on Supervisory Control and Data Acquisition (SCADA) won the second prize at the symposium conducted by the Electrical and Electronics Engineering department of the SRM University. Other topics on which I presented papers were
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LMS 算法源程序，绘制性能曲线图，误差性能曲线-LMS algorithm source code, rendering the performance curves, the error performance curve
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用标准C语言实现的基于DTW算法的特定人孤立词语音识别系统，能实现汉语数字0至9个语音发音的识别，具有很好的识别性能。-Using standard C language based on the DTW algorithm to achieve the specific words were isolated speech recognition system, to achieve Chinese figures 0-9 voice pronunciation recognition, wi
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识别正确率和抗噪性能是语音识别的研究重点，而识别响应速度也是决定系统实用化的关键 文章改进了传统的动态时间弯折算
法结构，将其应用于实时说话人辨识系统中，极大地提高了系统运行速度，随着待识别语音数目的增多，该算法优势更加明显 实验表明，
在不影响系统识别率的情况下，该方法使系统的运行速度平均提高了1.5 倍-Identify the correct rate and the anti-noise performance is the focus of speech recognition
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:高斯混合模型(GMM)是一种经典的说话人识别算法，本文在实现其算法的同时，主要模拟了不同噪声环境情况下高斯混合模型
(GMM)的杭嗓声性能，得到了一些有益结论。
-Gaussian mixture model (GMM) is a classic speaker recognition algorithms, this algorithm at the same time in fulfilling its main simulated environmental conditions
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为了提高语音分离算法的收敛速度以及分离性能，提出把拉普拉斯正态混合分布概率密度函数作为语音信号概率密度函数的估计，得到一个更加适合语音信号分离的激活函数，基于此函数提出一种快速语音分离算法.-In order to improve speech separation algorithm convergence speed and separation performance, raise the normal mixture distribution Laplace probability de
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语音增强是影响语音识别系统性能的重要成分。为了比较语音增强算法的性能，采用Matlab软件进行了数值仿真，对不同噪声环境下的语音用3种不同的方法进行降噪，采用信噪比、端点检测等方法来降噪效果，并对几种增强算法的性能进行了比较分析。结果表明，在变噪声环境下短时谱MMSE法最佳，谱减法和维纳滤波法各有优点。-Speech enhancement of voice recognition is an important component of system performance. In order
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高性能语音识别系统的实现！包括系统实现，算法实现等。研究语音识别的好书！-High-performance speech recognition system to achieve! Including system implementation, algorithm, etc. Speech recognition research books!
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实现FIR系统中的最小均方误差自适应滤波算法（LMS）,并通过误差曲面研究其性能。-FIR system in the minimum mean square error adaptive filtering algorithm (LMS), and study its performance through the error surface.
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传统的短时谱估计语音增强算法通常假设语音谱分量相互独立，没有考虑语音谱分量间的相关性。针对这
一问题，该文提出一种新的基于多元Laplace分布模型的短时谱估计算法。首先，假设语音的离散余弦变换(DCT)
系数服从多元Laplace分布，以此利用谱分量间的相关性；在此基础上，利用多元随机矢量的高斯尺度混合模型表
示，推导得到语音DCT系数矢量的最小均方误差(MMSE)估计的解析表达式；并进一步推导了基于该分布模型的
语音存在概率，对最小均方误差估计子进行修正。实验结果表明，该算法
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