抖音“换装秀”中的自我建构与他者认同——基于观展/表演范式

生产性受众通过抖音平台强大的传播作用,实现了成为扩散性用户这一转变。“换装秀”作为抖音生态中的短视频类型,拥有规模性的表演内容和粉丝认同,这一方面促进表演用户构建赋魅后的表演自我,在他者镜像中认识、完善真实个体,建构视觉文化景观,进而对现实环境产生影响;另一方面在被打造的传播情境中调动了观展用户的情感认同与对话联系,引发群体模仿,使得这一小众形式融入到抖音平台消费文化中。

QQ声音随心换

“嘣嘣嘣”、“嘀嘀嘀”,这些就是QQ默认的声音,天天听是不是有点烦?虽说在系统设置中可以更换,但是设置起来毕竟有些难度。 QQ换音大师是一款可轻松更换声音的软件,有多种声音可供选择,并且提供了几种组合,可以直接调用。软件安装卸载下载地址为:http://www.sai188.com/files/huanyin.exe,软件的安装很简单,直接运行下载文件,按照提示即可完成。

“咽音”练声法在艺术歌唱中的作用初探

“咽音”不是任何人凭天然的发声法或靠摹仿就能发出的声音，而是一种对咽部作特殊的调节后所发出的声音。“咽音”练习法象一种维生素，不是有药性的药，有药性的药是不能随便吃的，不对症下药可能是有害的，即使碰巧无害，也不大可能有益。维生素则不然，可随便吃无害，当然不能大量服用。通过这一比喻，我们就能更深层的了解“咽音”在歌唱中的作用。首先它能增强歌唱的持久力，改进音质，再就是能明显地增强发音的能力，不致产生换音现象。

论不同和声体系之间“和弦外音”相关概念的差异

在和声学理论中,不同体系的"和弦外音"常使用不同的概念,有时同一概念对应不同的实践形式,或同一实践具有不同的名称。这种非统一的概念甚至影响到和声理论应用时的统一表述。

论民间反语——兼说反切起源

反语,是用改变语音成分构成的一种民间隐语,又称倒语、切语、切口或切脚,两广一带久已有之,相当普及。例如《广西文史资料》第六辑载有冯璜《新桂系崛起百色的片断回忆》,文中提到:“我们和马晓军没有密码本联系,以是决定用容县地方方言的‘倒语’(反切)译成密码拍给马晓军,电报全文如下: 腊同(陆谭)蟹备(已败)统戚(请速)四羌(相机)苏半(宣布)习理(自立)因为缺少‘独立’两字的倒语可用,只好以自立二字替代。”这里所说的“倒语”就是一种“反语”,在容县及其附近的的北流、玉林及岑溪、藤县等地,至今仍在流行。

Seismic data denoising based on learning-type overcomplete dictionaries

The transform base function method is one of the most commonly used techniques for seismic denoising, which achieves the purpose of removing noise by utilizing the sparseness and separateness of seismic data in the transform base function domain. However, the effect is not satisfactory because it needs to pre-select a set of fixed transform-base functions and process the corresponding transform. In order to find a new approach, we introduce learning-type overcomplete dictionaries, i.e., optimally sparse data representation is achieved through learning and training driven by seismic modeling data, instead of using a single set of fixed transform bases. In this paper, we combine dictionary learning with total variation （TV） minimization to suppress pseudo-Gibbs artifacts and describe the effects of non-uniform dictionary sub-block scale on removing noises. Taking the discrete cosine transform and random noise as an example, we made comparisons between a single transform base, non-learning-type, overcomplete dictionary and a learning-type overcomplete dictionary and also compare the results with uniform and nonuniform size dictionary atoms. The results show that, when seismic data is represented sparsely using the learning-type overcomplete dictionary, noise is also removed and visibility and signal to noise ratio is markedly increased. We also compare the results with uniform and nonuniform size dictionary atoms, which demonstrate that a nonuniform dictionary atom is more suitable for seismic denoising.

SINGLE TONE JAMMING ELIMINATION SCHEME OF MULTICARRIER SPREAD SPECTRUM SYSTEM

The proposed scheme is based on Discrete Fourier Transform (DFT) domain processing. The key technology of this scheme is jamming parameters' accurate estimation and jamming reconstruction. Compared with the 'threshold exciser' scheme the proposed scheme can eliminate more jamming energy on the whole frequency band with the minimum loss of useful signal energy. As shown in the research and simulation, the proposed scheme is much better than the 'threshold exciser' scheme, especially in the case of high power jamming whereas the 'threshold exciser' scheme might be invalid.

A new formant feature and its application in Mandarin vowel pronunciation quality assessment

In order to improve the Mandarin vowel pronunciation quality assessment, a nox/el formant feature was proposed and applied to formant classification for Chinese Mandarin vowel pronunciation quality evaluation. Formant candidates of each frame were plotted on the time-frequency plane to form a bitmap, and its Gabor feature was extracted to represent the formant trajectory. The feature was then classified by using GMM model and the classification posterior probability was mapped to pronunciation quality grade. The experiments of comparing the Gabor transformation based formant trajectory feature with several other kinds of traditionally used features show that with this method, a human-machine scoring correlation coefficient （CC） of 0.842 can be achieved, which is better than the result of 0.832 by traditional speech recognition techniques. At the same time, considering that the long-term information of formant classification and the short-term information of speech recognition technique are complementary to each other, it is investigated to combine their results with linear or nonlinear methods to further improve the evaluation performance. As a result, experiments on PSK show that the best CC of 0.913, which is very close to the correlation of inter-human rating of 0.94, is gotten by using neural network.

Implementation of a Novel Algorithm on Acoustic Doppler Current Profiler Signal Processing System

Acoustic Doppler current profiler （ADCP） uses acoustic energy directed along narrow beams for current measurement. In conventional method, the quantity of sampling affects the precision of fast Fourier transform （FFT） algorithm, and the algorithm needs a large amount of data to process. A novel frequency estimator.enhanced least mean square （ELMS） algorithm for a single complex sinusoid in complex white Gaussian noise, is proposed in ADCP system. As sampling frequency equals 120 krad/s and the sampling number equals 240. the minimum resolving is 0. 5 krad/s. All variances keep 11.11%. ELMS algorithm needs less data than FFT. And the robust algorithm can estimate the spectrum true value to 99.9% when the signal to noise ratio （SNR） is equal to 0 dB. Experiments prove that the estimation values will diverge much from the ideal when SNR is less than -6 dB.

Probability Density and Statistical Properties for a Three-State Markovian Noise and Escape of Particles for a System Driven by This Noise

A three-state Markovian noise is investigated.Its probability density and statistical properties are obtained. Escape of particles for a system with potential barrier only driven by this noise is investigated.It is shown that,in some circumstances,this noise can make the particles escape over the potential barrier;but in other circumstances,it cannot. Resonant activation phenomenon appears for the system considered by us.

Analytical Study of Nonlinear Dust Acoustic Waves in Two-Dimensional Dust Plasma with Dust Charge Variation

The nonlinear dust acoustic waves in two-dimensional dust plasma with dust charge variation is analytically investigated by using the formally variable separation approach. New analytical solutions for the governing equation of this system have been obtained for dust acoustic waves in a dust plasma for the first time. We derive exact analytical expressions for the general case of the nonlinear dust acoustic waves in two-dimensional dust plasma with dust charge variation.

A CODEBOOK COMPENSATIVE VOICE MORPHING ALGORITHM BASED ON MAXIMUM LIKELIHOOD ESTIMATION

This paper presents an improved voice morphing algorithm based on Gaussian Mixture Model(GMM) which overcomes the traditional one in the terms of overly smoothed problems of the converted spectral and discontinuities between frames.Firstly, a maximum likelihood estimation for the model is introduced for the alleviation of the inversion of high dimension matrixes caused by traditional conversion function.Then, in order to resolve the two problems associated with the baseline, a codebook compensation technique and a time domain medial filter are applied.The results of listening evaluations show that the quality of the speech converted by the proposed method is significantly better than that by the traditional GMM method, and the Mean Opinion Score(MOS) of the converted speech is improved from 2.5 to 3.1 and ABX score from 38% to 75%.

Memory of Familiar Melodies： Comparison Between Original and Transposed Keys

The long-term memory for musical keys of familiar melodies was investigated. An experiment was conducted focusing on memory strength, music familiarity, and key transposition using musical pieces. Participants were eighty-one Japanese undergraduate and graduate students. Eight were absolute pitch （AP） possessors and seventy-three were non-AP possessors. Two pieces of well-known classical music were selected as stimuli. These pieces were played in seven different keys： One was an original key and the other six were transposed keys in which the linear distance and harmonic distance were varied. Participants rated their strength of long-term memory for a particular segment of well-known music by comparing it with their memory of this piece. Importantly they were not required to identify the musical key of the melody. Results indicated that the strength of memory for these musical segments depended mainly on the pitch range associated with the transposed piece and partially on its key. We discussed participants＇ memory of melodies in the light of linear distance between original and transposed keys, harmonic distance between these factors, and the possibility of absolute tonality.

Noise-Induced Transition in a Voltage-Controlled Oscillator Neuron Model

In the presence of Gaussian white noise,we study the properties of voltage-controlled oscillator neuronmodel and discuss the effects of the additive and multiplicative noise.It is found that the additive noise can accelerate andcounterwork the firing of neuron,which depends on the value of central frequency of neuron itself,while multiplicativenoise can induce the continuous change or mutation of membrane potential.

Relationship between magnetic Barkhausen noise and the stresses, the hardness and the phase content of ferromagnetic materials

Magnetic Barkhausen Noise (MBN) is a phenomenon of electromagnetic energy emission due to the movement of magnetic domain walls inside ferromagnetic materials when they are locally magnetized by an alternating magnetic field. According to Faraday’s law of electromagnetic induction, the noise can be received by the coil attached to the surface of the material being magnetized and the noise carries the message of the characteristics of the material such as stresses, hardness, phase content, etc. Based on the characteristic of the noise, research about the relationship between the welding stresses in the welding assembly and the noise, the fatigue damage of the plate structure and the noise, and the influence of heat treatment and the variation of phase content to the noise are carried out in this paper.

Extraction of failure characteristic of rolling element bearing based on wavelet transform under strong noise

There has been a lot of research has been performed regarding diagnosing rolling element bearing faults using wavelet analysis, but almost all methods are not ideal for picking up fault signal characteristics under strong noise. Therefore, this paper proposes auto-correlation, cross-correlation and weighted average fault diagnosis methods based on wavelet transform (WT) de-noising which combine correlation analysis with WT for the first time. These three methods compute the auto-correlation, the cross-correlation and the weighted average of the measured vibration signals, then de-noise by thresholding and computing the auto-correlation of de-noised coefficients of WT and FFT of energy sequence. The simulation results indicate that all methods enhance the capabilities of fault diagnosis of rolling bearings and pick up the fault characteristics effectively.

Audio Zero-Watermark Scheme Based on Discrete Cosine Transform-Discrete Wavelet TransformSingular Value Decomposition

Traditional watermark embedding schemes inevitably modify the data in a host audio signal and lead to the degradation of the host signal.In this paper,a novel audio zero-watermarking algorithm based on discrete wavelet transform(DWT),discrete cosine transform(DCT),and singular value decomposition(SVD) is presented.The watermark is registered by performing SVD on the coefficients generated through DWT and DCT to avoid data modification and host signal degradation.Simulation results show that the proposed zero-watermarking algorithm is strongly robust to common signal processing methods such as requantization,MP3 compression,resampling,addition of white Gaussian noise,and low-pass filtering.

Blind Separation of Speech Signals Based on Wavelet Transform and Independent Component Analysis

Speech signals in frequency domain were separated based on discrete wavelet transform (DWT) and independent component analysis (ICA). First, mixed speech signals were decomposed into different frequency domains by DWT and the subbands of speech signals were separated using ICA in each wavelet domain; then, the permutation and scaling problems of frequency domain blind source separation (BSS) were solved by utilizing the correlation between adjacent bins in speech signals; at last, source signals were reconstructed from single branches. Experiments were carried out with 2 sources and 6 microphones using speech signals at sampling rate of 40 kHz. The microphones were aligned with 2 sources in front of them, on the left and right. The separation of one male and one female speeches lasted 2.5 s. It is proved that the new method is better than single ICA method and the signal to noise ratio is improved by 1 dB approximately.

Stochastic Resonance of Instantaneous-State in Linear Regime of Single-Mode Lasers Driven by Colored Noises

According to a linear equation of the laser intensity of single-mode laser with input signal, we compute the generalized signal-to-noise ratio （GSNR） in the instantaneous-state of the single-mode laser, which is driven by two colored noises and correlated in the form of an e-exponential function. We detect that the stochastic resonance （SR） also occurs on instantaneous state at any time. Furthermore we discuss the GSNR trend to stable state in three different forms when taking different signal frequencies.

Spatially Periodic System with Infinite Globally Coupled Oscillators Driven by Temporal-Spatial Noise

In this paper, we study spatially periodic system with infinite globally coupled oscillators driven by temporal-spatial noise and subject to a constant force. The results show that the system exhibits the phenomena of the non-equilibrium phase transition, transport of particles, and the anomalous hysteresis cycle for the mean field and the probability current.