拖拉机发动机信号降噪与分离处理新方法

介绍了一种处理信号的新方法——模式滤波法,将该方法应用于拖拉机发动机信号的处理中,可实现信号与噪声合理、完整的分离,不仅为有效地去除发动机信号中的噪声奠定了基础,也为拖拉机发动机的故障诊断研究提供了理论参考。

改进的混合激励线性预测编码算法

针对混合激励线性预测编码中子带声音强度的硬判决导致激励源欠精细问题,将子带声音强度视为5维的模糊特征矢量,用改进的LBG算法设计码本并用5bit对其作矢量量化;以精细量化的子带声音强度调制带通滤波器,以此获取精细的混合激励信号,最终达到改善合成语音质量的目标。仿真实验表明:改进算法能有效地改善合成语音的自然度。

Discriminative tone model training and optimal integration for Mandarin speech recognition

Two discriminative methods for solving tone problems in Mandarin speech recognition are presented. First, discriminative training on the HMM （hidden Markov model） based tone models is proposed. Then an integration technique of tone models into a large vocabulary continuous speech recognition system is presented. Discriminative model weight training based on minimum phone error criteria is adopted aiming at optimal integration of the tone models. The extended Baum Welch algorithm is applied to find the model-dependent weights to scale the acoustic scores and tone scores. Experimental results show that tone recognition rates and continuous speech recognition accuracy can be improved by the discriminatively trained tone model. Performance of a large vocabulary continuous Mandarin speech recognition system can be further enhanced by the discriminatively trained weight combinations due to a better interpolation of the given models.

Speech enhancement through voice activity detection using speech absence probability based on Teager energy

In this work, a novel voice activity detection （VAD） algorithm that uses speech absence probability （SAP） based on Teager energy （TE） was proposed for speech enhancement. The proposed method employs local SAP （LSAP） based on the TE of noisy speech as a feature parameter for voice activity detection （VAD） in each frequency subband, rather than conventional LSAP. Results show that the TE operator can enhance the abiTity to discriminate speech and noise and further suppress noise components. Therefore, TE-based LSAP provides a better representation of LSAP, resulting in improved VAD for estimating noise power in a speech enhancement algorithm. In addition, the presented method utilizes TE-based global SAP （GSAP） derived in each frame as the weighting parameter for modifying the adopted TE operator and improving its performance. The proposed algorithm was evaluated by objective and subjective quality tests under various environments, and was shown to produce better results than the conventional method.

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 Particle Filter Based Compressive Sensing Method for Tracking Moving Wideband Sound Sources

Tracking moving wideband sound sources is one of the most challenging issues in the acoustic array signal processing which is based on the direction of arrival(DOA) estimation. Compressive sensing(CS) is a recent theory exploring the signal sparsity representation, which has been proved to be superior for the DOA estimation. However, the spatial aliasing and the offset at endfire are the main obstacles for CS applied in the wideband DOA estimation. We propose a particle filter based compressive sensing method for tracking moving wideband sound sources. First, the initial DOA estimates are obtained by wideband CS algorithms. Then, the real sources are approximated by a set of particles with different weights assigned. The kernel density estimator is used as the likelihood function of particle filter. We present the results for both uniform and random linear array. Simulation results show that the spatial aliasing is disappeared and the offset at endfire is reduced. We show that the proposed method can achieve satisfactory tracking performance regardless of using uniform or random linear array.

Female Voice Interpretation of The House on Mango Street in the View of Synaesthesia

In The House on Mango Street, American ethnic Mexican female writer Sandra Cisneros probes into Latino American’s collective identity and Latinas’ gender identity. Literature and psychology has been linked together starting from Plato and Aristotle period. In the neuropsychological domain, synaesthesia allows people to combine several perceptions together; while in literature, it magically melts the “voice” of the author’s into the works. To interpret the female voice of the book, this article analyzes the voice of poverty and distress, of pursuing ethnic equality, and of pursuing female independence, on the basis of the psychological perception, synaesthesia, so as to reveal Sandra Cisneros’s feminist voice on the reflections of ethnic Mexican female values by her beautiful naive poetic language, with a pure and innocent tone.

Extraction of Partial Discharge Acoustic Signal by Wavelet Transform with Teager′s Energy Operator

To develop a measurement system for monitoring partial discharge （PD） without the effect of external interferences,an algorithm of PD signal extraction based on wavelet transform with Teager＇s energy operators was presented. Acoustic signal generated by PD was selected to remove excessive interfering signals and electromagnetic interferences. Acoustic signals were collected and decomposed into I0 levels by wavelet transform into approximation and detail components. “Daubechies 25” was proved to be the most suitable mother wavelet for the extraction of PD acoustic signals. Compared with conventional wavelet denoising method, Teager＇s energy operators were adopted to the PD signal reconstruction and the signal to noise ratio was in creased by 20%-25% inthe experiment,without lost in energy and pulse amplitude.

Tonal Noise Prediction of an Automotive Engine Cooling Fan： Comparison between Analytical Models and Acoustic Analogy Results

Valeo, involved in engine cooling fan system design for many years, is interested in noise prediction tools for axial fans. Thus, this paper describes a two-part study of tonal noise computation. The first part deals with the prediction of tonal noise using analytical models. As for the second part, it describes a hybrid approach for predicting tonal noise where the sources are extracted from an Unsteady Reynolds-Averaged Naviers-Stocks （URANS） simulation and then propagated into the far, free field using the Ffowcs Williams and Hawkings＇ acoustic analogy. The computational domain is meshed with 46 million polyhedral elements and the simulation takes into account the exact geometry of the rotor blades, the stator blades and the shroud. The results from the first part show that analytical models can be used for comparisons between different fan geometries, but are unable to provide accurate noise predictions compared to experimental results. The simulation shows non-periodic blade loading over a whole fan revolution, and different blade loading between the blades. This introduces some bias in the assessment of the acoustic performance of the fan. Overall, the results from the hybrid method are in accordance with the experimental results.

Fault tolerant two-step quantum secure direct communication protocol against collective noises

This work proposes two fault tolerant quantum secure direct communication （QSDC） protocols which are robust against two kinds of collective noises： the collective-dephasing noises and the collective-rotation noises, respectively. The two QSDC protocols are constructed from four-qubit DF states which consist of two logical qubits. The receiver simply performs two Bell state measurements （rather than four-qubit joint measurements） to obtain the secret message. The protocols have qubit efficiency twice that of the other corresponding fault tolerant QSDC protocols. Furthermore, the proposed protocols are free from Trojan horse attacks.