基于AAC比特流的音频信号Hiss噪声抑制方法

基于AAC比特流,提出了一种压缩域音频Hiss噪声抑制方法。该方法的输入为含噪音频的AAC比特流,输出为增强音频的AAC比特流。首先,利用修正的绝对中值标准差（MMAD, modified median absolute deviation）估计Hiss噪声,其次,利用修正的离散傅里叶变换（MDFT, modified discrete Fourier transform）计算听觉掩蔽阈值参数,最后,根据参数软阈值方法得到增强的AAC比特流,并用于AAC解码器得到最终的增强音频信号。主观和客观测试结果表明,所提出的方法能有效去除AAC解码音频信号中的Hiss噪声,其性能明显优于现有的几种Hiss噪声消除方法。     

基于H.264/AVC的音视频同步压缩方法

利用H.264/AVC标准中DCT系数的奇偶特性.在编码端将音频比特流嵌入到视频DCT系数中一起压缩传输,在解码端解出视频同时根据相应算法提取出音频信息,从而实现音视频的同步压缩.实验表明该方法在不增加数据量的前提下,可以无失真地还原出音频信号,对视频质量影响很小.     

基于自适应阈值正交小波变换兰姆波去噪方法

提出了基于自适应阈值正交小波变换兰姆波去噪方法 （WT-AL）。首先利用正交小波变换降低含噪兰姆波信号的自相关性,然后利用自适应阈值方法自适应地对不同尺度的正交小波变换系数进行阈值处理,最后利用小波重构获得重构信号。实验结果表明：该方法去噪后信号信噪比明显提高,均方误差明显降低。     

混沌信号的自适应阈值同步挤压小波变换消噪

针对同步挤压小波变换（SST）消噪过程中仅使用单一阈值的不足,对SST消噪时的幅度阈值进行了改进,提出了一种基于SST分层阈值的混沌信号消噪方法.首先,根据信号和噪声经SST分解后系数的分布模型,推导SST混沌去噪时幅度阈值权系数的均方误差计算公式;进而,根据均方误差最小准则,计算幅度阈值权系数的最优取值;最后,根据最优阈值权系数和噪声标准差,确定SST混沌去噪时的分层阈值.利用模拟混沌信号和实测月太阳黑子信号对所提方法进行了实验分析,实验结果表明,本文方法可较好地滤除混沌信号中的噪声,同时原始信号的内在混沌特性也能得到较大程度的恢复.与小波阈值法和集合经验模态分解（EEMD）消噪法相比,可获得更好的消噪效果.     

基于Δ-Σ调制技术的无线音频传输装置

本文针对有线音频传输的存在信号损耗和干扰问题,提出一种基于Δ-Σ调制技术的无线音频数字传输方案,方案利用Δ-Σ调制器对音频信号进行采集,将采集得到的高速比特流数据通过红外光的形式向外无线传输。同时为了增加接收面积,方便解决发送、接收的对准问题,利用太阳能电池对光信号进行检测和提取,光电转换后得到的接收信号经模拟开关和切比雪夫滤波器后完成音频信号的还原。实验数据表明,该方案结构简单,成本低,同时信号失真小。本文网络版地址：http：//www.eepw. com.cn/article/264523.htm     

基于信号相位差和后置滤波的语音增强方法

 在复杂的声学环境中,通常噪声场特性和混响强度是未知的,这样就对麦克风阵列语音增强算法的性能提出了较高的要求.本文提出一种基于带噪语音信号相位差和后置滤波的语音增强方法.首先,将麦克风阵列接收信号分帧,利用相邻两个麦克风之间每帧带噪语音信号的相位差,构成该帧改变频率点幅度谱值的比例系数,对该帧带噪语音信号进行掩蔽增强处理,得到预处理信号;然后利用固定波束形成、独立分量分析算法和后置滤波技术对预处理信号进一步处理,从而有效地抑制了噪声.计算机仿真实验结果表明,在存在一定混响的多种噪声场中,该方法均具有较好的噪声抑制能力.     

非线性阈值自调整小波图像去噪方法研究

为解决小波变换阙值去噪方法中阙值的合理选取，提出一种基于非线性阙值自调整小波变换的图像去噪方法。在传统小波阈值去噪方法的基础上，结合神经网络的非线性双曲线正切函数和BP训练方法，首先对含噪图像进行二进小波分解，然后对分解系数进行小波重建，并将重建系数在BP神经网络中采用最速梯度下降法进行优化处理，得到最优阈值，最后对阈值处理的重建系数进行叠加，得到原始图像信号的估计值，即去噪后的图像信号。仿真实验表明，该方法具有较好的重建图像视觉效果，信噪比（SNR）和峰值信噪比（PSNR）均比传统小波阈值方法提高了1～2dB。     

基于小波分析的语音信号增强的研究

语音增强目的是从带噪语音中尽可能纯净的原始语音,即消除含噪语音信号中的噪声成份,提高输入信号的信噪比.在实际应用环境中,语音都会不同程度受到噪声的干扰,噪声会影响语音质量,严重的情况下将语音完全淹没到噪声中,无法分辨.本文将读入的语音信号加入正态随机噪声,然后对含噪声的语音信号进行小波分解,估计噪声的方差,然后获取去噪的阈值并对小波分解的高频系数进行阈值量化,得到去噪后的语音信号.仿真证明此方法具有很好的增强效果.     

基于Laplace分布的非下采样小波包脉冲星信号消噪

为了提高脉冲星信号的去噪效果,提出了一种基 于非下采样小波包(NWP)分解的局部Laplace模型消噪方法。 首先对真实脉冲星信号进行NWP分解,统计真实脉冲星信号NWP系数的分布特性, 建立真实脉冲星信号小波包系数的Laplace分布模型;然后在Laplace先验概率分布的基础 上,根据最大后 验概率(MAP)估计准则,利用含噪脉冲星信号的小波包系数对真实脉冲星信号的小波包系数 进行有效估算;最后 对估算出的小波包系数进行NWP重构,得到消噪后的脉冲星信号。采用不同 的脉冲星信号进行实 验分析的结果表明,与经典的基于高斯分布的非下采样小波(NSW)消噪和NWP消噪相比,本文 方法可以 更有效地去除噪声,同时更好地保留信号中的微脉冲等细节信息,在信噪比(SNR)、均方根误差(RMSE)、相关系数(CC)和峰值相对误差(REPV)等都 有较好的改善。     

基于小波变换的自适应语音盲分离新算法

提出用小波变换和两步自适应盲分离算法相结合的方法来进行语音分离.首先,利用小波变换分别对各含噪混叠语音进行消噪;然后,利用代价函数的极值点特性分别获得混合信号和白化信号的特征向量矩阵,实现自适应盲分离过程;最后,进一步对分离信号进行矢量归一和再消噪处理,得到各个语音源信号的最终估计.实验结果表明此方法取得了很好的分离效果.     

A noise reduction technique of speech signal using ICA and spectral analysis

This paper discusses the new method on noise reduction exploiting the combined effects of wavelet decomposition, ICA and spectral analysis on noisy speech. The input noisy speech is wavelet decomposed into two signals. Wavelet entropy is computed based on the modified probability density function for the signal derived from the approximation coefficients during wavelet decomposition. By proper entropy comparison, the starting frame is detected. Between the two signals obtained from the wavelet decomposition, one is speech combined with noise and another one is noise alone. These two signals are analysed in independent component analysis (ICA) domain, in order to generate an enhanced speech. Zero-crossing rate is computed and used to discriminate between speech and noise. Then, spectral analysis is performed on the noise prior to starting frame and noisy speech. Elimination of noise frequencies in the noisy speech leads to noise reduced speech. Subjective analysis and experimental results show the considerable noise reduction capability of the proposed algorithm.     

Common Architecture Design of Novel Recursive MDCT and IMDCT Algorithms for Application to AAC, AAC in DRM, and MP3 Codecs

This paper presents a novel recursive algorithm to compute the modified discrete cosine transform (MDCT) and the inverse MDCT (IMDCT) based on type IV of the discrete cosine transform (DCT-IV) algorithm. The proposed algorithm has the following advantages: In contrast with parallel designs, the input sequence fed by serial in/serial out (SISO) can dynamically be switched with the variable window length. The data throughput per transformation for the MDCT and IMDCT algorithms is four times higher than that of the previous algorithms, and the ROM size can be reduced by 50%-79%. Less memory is required for accessing; thus, it can reduce the chip area in hardware implementation. The chip efficiency is also increased, and the proposed architecture makes a feasible design to integrate several audio standards [i.e., advanced audio coding (AAC)/AAC in digital radio mondiale (DRM/MPEG-1 Audio Layer 3 (MP3)] into one portable media player. The proposed algorithm is designed and fabricated by using 0.18-mum 1P6M complimentary metal-oxide-semiconductor (CMOS) process. The core area is 441 times 437 mum², including the MDCT, IMDCT, and DCT-IV modules. For modern audio applications, i.e., AAC/AAC in DRM/MP3, this processor only consumes 14.077/3.482/0.3138 mW at 50/12.5/1 MHz. Furthermore, the proposed algorithm can calculate the 2048/1920/256/240/36/12-point MDCT and the 1024/960/128/120/18/6-point IMDCT.     

Nonlinear cepstral equalisation method for noisy speech recognition

The authors deal with the problem of automatic speech recognition in the presence of additive white noise. The effect of noise is modelled as an additive term to the power spectrum of the original clean speech. The cepstral coefficients of the noisy speech are then derived from this model. The reference cepstral vectors trained from clean speech are adapted to their appropriate noisy version to best fit the testing speech cepstral vector. The LPC coefficients, LPC derived cepstral coefficients, and the distance between test and reference, are all regarded as functions of the noise ratio (the spectral power ratio of noise to noisy speech). A gradient based algorithm is proposed to find the optimal noise ratio as well as the minimum distance between the test cepstral vector and the noise adapted reference. A recursive algorithm based on Levinson-Durbin recursion is proposed to simultaneously calculate the LPC coefficients and the derivatives of the LPC coefficients with respect to the noise ratio. The stability of the proposed adaptation algorithm is also addressed. Experiments on multispeaker (50 males and 50 females) isolated Mandarin digits recognition demonstrate remarkable performance improvements over noncompensated method under noisy environment. The results are also compared to the projection based approach, and experiments show that the proposed method is superior to the projection approach under a severe noisy environment     

一种自适应语音增强均衡器的研究

在参考滤波器组的基础上，提出一个用于语音和音频信号进行时不变或自适应谱修正的数字滤波器结构，主要用于音频信号均衡和降噪。在频域计算滤波器系数的同时，信号在时域滤波。与通常频域处理相比，在信号延迟、原型滤波器设计、复杂性等方面，该结构有良好的特性。该算法既适用于均匀频率分辨率，也适用于非均匀频率分辨率。     

基于MELMD-ICA的光纤振动信号降噪方法

针对分布式光纤传感系统所采集含噪信号,提出一种改进集成局部均值分解(MELMD)联合独立成分分析(ICA)的降噪方法,引入排列熵判决机制提高抑制模态混叠与虚假分量能力。首先使用MELMD方法分解含噪信号得到乘积函数(PF)并进行信号重构;将含噪信号和重构信号求差得到虚拟噪声,构造虚拟通道;然后使用ICA对含噪信号和虚拟通道进行信噪分离,得到最终结果。通过实验验证,该方法与EMD-ICA,EEMD-ICA,MELMD相比,能更好地消除信号中的噪声,保留信号的特征信息。     

A 128 Kb/s Hi-Fi audio codec based on adaptive transform codingwith adaptive block size MDCT

A Hi-Fi audio codec with an improved adaptive transform coding (ATC) algorithm is presented using digital signal processors (DSPs). An audio signal with a 20 kHz bandwidth sampled at 48 kHz is coded at a rate of 128 kb/s. The algorithm utilizes adaptive block size selection, which is effective for preecho suppression. A modified discrete cosine transform (MDCT) with a simple window set is employed to reduce block boundary noise without decreasing the performance of transform coding. In addition, a fast MDCT calculation algorithm, based on a fast Fourier transform, is adopted. Weighted bit allocation is employed to quantize the transformed coefficients. The codec was realized by a multiprocessor system composed of newly developed DSP boards. Subjective tests with the codec show that the coding quality is comparable to that of compact disc signals     

Robust Audio Fingerprinting Method Using Prominent Peak Pair Based on Modulated Complex Lapped Transform

The robustness of an audio fingerprinting system in an actual noisy environment is a major challenge for audio‐based content identification. This paper proposes a high‐performance audio fingerprint extraction method for use in portable consumer devices. In the proposed method, a salient audio peak‐pair fingerprint, based on a modulated complex lapped transform, improves the accuracy of the audio fingerprinting system in actual noisy environments with low computational complexity. Experimental results confirm that the proposed method is quite robust in different noise conditions and achieves promising preliminary accuracy results.