基于K-L距离的两步固定音频检索方法

根据音频文件数据量大、数据间存在一定相关性的特点,提出一种基于K-L距离的两步固定音频检索方法。该方法采用基于可变门限的直方图检索方法快速筛选出相似度较高的语音文件,利用特征矩阵的K-L距离对剩余语音进行精确比较,取得较好的效果。实验结果证明,该方法能使检索准确率达到90%左右。     

语音信号中字词端点检测方法的两项改进

为了提高传统字词端点检测方法检测端点的准确性,分析了传统检测方法的不足,针对语音信号直流分量不为零和长音节尾音被误切割等特殊情况,提出了字词端点检测改进措施。经实验,改进措施有较好实用效果。     

The effect of nonhuman’s external regulation on detecting the natural development process of young children’s self-regulation during learning tasks

The present study explored the effect of nonhuman’s external regulation on children’s natural development of self-regulation and the effect of each natural developed class on children’s spontaneous thinking aloud and satisfaction. The Aginian’s methodology (Agina et al., 2011a) that relied on special computer agents for the external regulation, measuring self-regulation and children’s satisfaction, and producing the final results in points was used with 40 preschool children, which were divided into classes based on their natural development of self-regulation during learning tasks. The results showed that children who followed Piagetian’s view were outperforming children who followed Vygotskyian’s view and Aginian’s view, which is a new psychological view generated by computer indicates that the child either followed unknown class of self-regulation’s natural development or the child holds an ambiguous psychological problem. The results also showed that the relationship between children’s spontaneous thinking aloud and children’s self-regulation is a reverse. The supplemental analysis showed that computer, as a nonhuman external regulator, can identify those children who hold psychological problems and can integrate the net signed of self-regulation of each child at each task through embedding the mathematics integration where the computer becomes fully conscious with all the occurrences of children’s behavioral regulation.     

一种多特征语音端点检测算法及实现

提出了一种应用语音的多个特征参量的语音端点检测算法,经过计算机模拟得到了比较满意的检测效果。并用基于DSP芯片的电路来硬件实现,在系统中能够实现通话方语音对通话过程的自动控制。     

基于DSP实现语音端点检测

介绍了一种以DSP芯片为核心的语音端点检测模块，用于有线／无线自动转接设备。所采用的语音端点检测算法应用多个语音特征参量进行联合检测，达到了比较满意的端点检测效果。该模块应用于系统中能够实现通话方语音对通话过程的自动控制。     

基于CEEMDAN-ZCR的光纤电流互感器非线性误差识别

针对光纤电流互感器(FOCT)漂移、变比波动等非线性误差问题,提出了一种基于自适应噪声完备集合经验模态分解(CEEMDAN)-过零率(ZCR)的光纤电流互感器误差识别算法。首先,利用CEEMDAN算法对光纤电流互感器输出电流信号进行分解,得到包含非线性误差特征的固有模态分量(IMF),构成原始误差向量数据集。然后,对比不同误差下的分量数量,利用ZCR算法计算不同误差下各个IMF分量的过零率指标,用于将IMF分类。最后,根据ZCR指标呈现出的特点,将IMF分量信号分为三类,并叠加重组为三个分量,构建出分解结果数量稳定的IMF分量信号,根据不同分量的特征实现误差识别。结果表明：基于CEEMDAN-ZCR的误差识别算法能够有效的识别两种误差,其中漂移误差特征主要集中在IMF中第三层,变比误差主要集中在IMF中第二层,验证了本方法的有效性。     

The effect of nonhuman’s external regulation on children’s responses to detect children with developmental problems (DP) associated with the natural development of self-regulation during learning tasks

The present study sought to examine the effect of the nonhuman’s external regulation on children’s responses during learning tasks to detect children with developmental problems (DP) associated with the natural development process of self-regulation. The material was an isolated, computer-based learning system that acts as a standalone learning environment and used by 100 preschool children, which were randomly selected from ten preschools without revising their medical files. Participants were classified by the system itself during learning progression in three essential groups based on Aginian’s zone of children regulation (ZCR), which is “the equilibrium point in the self-regulation’s development process that controls the child to be either a self-Vygotskyian’s learner, self-Piagetian’s learner, or self-Aginian’s learner during learning tasks” ( Agina, Kommers, & Steehouder, 2011d). The results showed that the preschool children can spontaneously do diagnostic tests during learning tasks and the nonhuman external regulator was able to analysis children’s responses that, in turn, used for detecting those children with DP. This result was practically confirmed by revising all children’s medical files that matched the final judgment of the nonhuman external regulator. However, the results confirmed that the natural development of self-regulation was fluctuated among three paradoxical views (Vygotskyian vs. Piagetian vs. Aginian).     

一种基于随机段的固定音频检索方法

在固定音频检索的整体检索方法中,当检索目标较长时,检索时间会变得很长。为了减小检索时间,提出了一种基于随机段的音频检索方法。把整个检索过程分成随机段检索和整体匹配两个阶段：随机段检索是从参考模板中随机选择一段（随机段）作为检索目标进行检索;整体匹配是在随机段检索出的基础上,判断潜在目标信号是否为参考模板。把这种随机检索的方法应用到计算特征距离和直方图交集方法中,结果证明该检索方法的准确率可以达到90%以上,而且平均检索时间可以降低到随机段与参考模板的比值和整体检索时间的积。     

一种语音端点检测方法的探究

研究了一种以过零率ZCR和能量E为特征的语音端点检测方法。在进行大量实验的基础上，经过分析，对该方法提出了几点改进。     

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.