An objective quality assessment method for bit-reduction coding of wideband speech.

This paper proposes a new objective quality assessment method for bit-reduction coding of wideband speech taking into account the masking effect of quantizing noise. First, this paper analyzes the reliability and sensitivity of the speech quality assessment method, based on a paired-comparison test with a modulated noise reference signal, for the bit-reduction coding of high-quality wideband speech. Then, the perception of quantizing noise is studied using speech with noise synthesized similar to the quantizing noise. The detection of quantizing noise is found to be influenced by masking by the source signal. This leads to a new method of objectively estimating the quality of coding speech by multiple regression analysis. The factors for the estimation are segmental signal-to-noise ratio, spectrum envelope distance between source signal and quantizing noise, and the similarity of the noise power envelope to the source signal in the time domain. This estimation method is applied to the parameter optimization of wideband coding systems.     

Conversational quality evaluation of artificial bandwidth extension of telephone speech

Artificial bandwidth extension methods have been developed to improve the quality and intelligibility of narrowband telephone speech and to reduce the difference with wideband speech. Such methods have commonly been evaluated with objective measures or subjective listening-only tests, but conversational evaluations have been rare. This article presents a conversational evaluation of two methods for the artificial bandwidth extension of telephone speech. Bandwidth-extended narrowband speech is compared with narrowband and wideband speech in a test setting including a simulated telephone connection, realistic conversation tasks, and various background noise conditions. The responses of the subjects indicate that speech processed with one of the methods is preferred to narrowband speech in noise, but wideband speech is superior to both narrowband and bandwidth-extended speech. Bandwidth extension was found to be beneficial for telephone conversation in noisy listening conditions.     

New cephalostat for speech physiology research

A device for stabilizing a subject's head is described which does not depend on earposts, allows for voluntary evacuation by the subject, and can be constructed at low cost. This particular cephalostat is used currently for stabilizing the head in studies of speech production where lip and jaw transduction devices, mounted external to the subject, are employed.     

Edge-detection algorithm based on DCT continuous extension technique

A new computational approach to the edge-detection problem, based on the continuous extension of discrete cosine transform (CEDCT) technique is proposed. This technique has some attractive properties, and other things being equal, it has more precise results than the usual discrete Fourier or discrete cosine transforms, especially at the intermediate points. That is why this technique allows one to estimate numerically a finite number of a derivatives of a discrete set of multidimensional points, using some specified properties of CEDCT. Because of using the spectrum of a given set of points, this approach is applicable to a wide area of signal-and image-processing problems. The results obtained by the proposed approach are compared with the well-known and widely used Canny algorithm. Some 1D and 2D numerical examples are given. The text was submitted by the authors in English.     

An approach based on simplified KLT and wavelet transform for enhancing speech degraded by non-stationary wideband noise

It is well known that the non-stationary wideband noise is the most difficult to be removed in speech enhancement. In this paper a novel speech enhancement algorithm based on the dyadic wavelet transform and the simplified Karhunen-Loeve transform (KLT) is proposed to suppress the non-stationary wideband noise. The noisy speech is decomposed into components by the wavelet space and KLT-based vector space, and the components are processed and reconstructed, respectively, by distinguishing between voiced speech and unvoiced speech. There are no requirements of noise whitening and SNR pre-calculating. In order to evaluate the performance of this algorithm in more detail, a three-dimensional spectral distortion measure is introduced. Experiments and comparison between different speech enhancement systems by means of the distortion measure show that the proposed method has no drawbacks existing in the previous methods and performs better shaping and suppressing of the non-stationary wideband noise for speech enhancement.     

CCD在光学镀膜宽带膜厚监控系统中的应用研究

讨论了 CCD的主要特性及对宽带膜厚监控系统的影响 ,介绍了典型的 CCD数据采集系统。建立了一套基于 CCD的宽带膜厚监控系统 ,并对该系统进行了光谱标定及光谱补偿 ,给出了提高信噪比及减小非线性影响的处理方法。     

改进的噪声鲁棒语音稀疏线性预测算法

语音线性预测分析算法在噪声环境下性能会急剧恶化,针对这一问题,提出一种改进的噪声鲁棒稀疏线性预测算法。首先采用学生t分布对具有稀疏性的语音线性预测残差建模,并显式考虑加性噪声的影响以提高模型鲁棒性,从而构建完整的概率模型。然后采用变分贝叶斯方法推导模型参数的近似后验分布,最终实现噪声鲁棒的稀疏线性预测参数估计。实验结果表明,与传统算法以及近几年提出的基于l_1范数优化的稀疏线性预测算法相比,该算法在多项指标上具有优势,对环境噪声具有更好的鲁棒性,并且谱失真度更小,因而能够有效提高噪声环境下的语音质量。     

An improved algorithm for noise-robust sparse linear prediction of speech

The performance of linear prediction analysis of speech deteriorates rapidly under noisy environments.To tackle this issue,an improved noise-robust sparse linear prediction algorithm is proposed.First,the linear prediction residual of speech is modeled as Student-t distribution,and the additive noise is incorporated explicitly to increase the robustness,thus a probabilistic model for sparse linear prediction of speech is built.Furthermore,variational Bayesian inference is utilized to approximate the intractable posterior distributions of the model parameters,and then the optimal linear prediction parameters are estimated robustly.The experimental results demonstrate the advantage of the developed algorithm in terms of several different metrics compared with the traditional algorithm and the l₁ norm minimization based sparse linear prediction algorithm proposed in recent years.Finally it draws to a conclusion that the proposed algorithm is more robust to noise and is able to increase the speech quality in applications.     

Dielectric-loaded wideband gyro-TWT

The bandwidth of a gyro-TWT (traveling-wave tube) can be widened by employing a dielectric-loaded waveguide to reduce the circuit's dispersion. Fast wave interaction allows the requirements on the beam's quality to be relaxed compared with slow wave interaction. A low-α (≡ν_⊥/ν_z) electron beam is chosen to avoid the absolute instability and minimize the possibility of dielectric charging. This device is investigated using a self-consistent single-mode, large-signal simulation based on a slow time scale formulation. Simulation results show that a constant drive bandwidth of 20% can be achieved for a 100 kV, 5 A electron beam with a velocity ratio of α=0.59 and an axial velocity spread of 2.0%. The growth rate is relatively low because of the low α of the electron beam. The design of a proof-of-principle experiment is described. The tube is expected to deliver a power of 80 kW from 9 to 11 GHz with 15% efficiency and a saturated gain of 30 dB. The performance of a single-anode magnetron injection gun designed to produce the required high-quality electron beam has been studied through simulation     

Compact wideband antenna above a wideband non-uniform artificial magnetic conductor

A compact wideband antenna place above a non-uniform artificial magnetic conductor (AMC) is presented. The antenna is composed of a wideband coplanar waveguide fed antenna, with wideband harmonic suppression characteristic using non-uniform defected ground structure. Besides, a non-uniform wideband AMC is designed. The AMC unit cell is composed of a square patch into which a four arms spiral shape is etched. It exhibits a wider ±90° bandwidth than the spiral unit cell and a smaller size than the square patch unit cell. The antenna is placed above the proposed AMC structure formed by 6 × 5 unit cells. The overall dimensions of the complete structure are 0.7 × 0.6 λ ₀ ² , where λ ₀ is the free-space wavelength at the lowest frequency. It offers a low-profile configuration with a total thickness of λ ₀/14.3, and it is matched between 2.5 and 5.4 GHz (73.5 %). Furthermore, it has a stable main lobe radiation pattern in the E- and H-planes within the operating frequency band. Moreover, compared with the antenna without AMC, the broadside realized gain is significantly increased. A prototype has been realized, and there is a good agreement between simulated and measured results. Furthermore, the proposed structure presents a size reduction of about 34 %, and better radiation characteristics in comparison with the conventional square AMC.     

Recognition of practical speech emotion using improved shuffled frog leaping algorithm

Due to the drawbacks in Support Vector Machine（SVM）parameter optimization,an Improved Shuffled Frog Leaping Algorithm（Im-SFLA）was proposed,and the learning ability in practical speech emotion recognition was improved.Firstly,we introduced Simulated Annealing（SA）,Immune Vaccination（Iv）,Gaussian mutation and chaotic disturbance into the basic SFLA,which bManced the search efficiency and population diversity effectively.Secondly,Im-SFLA Was applied to the optimization of SVM parameters,and an Im-SFLA-SVM method Was proposed.Thirdly,the acoustic features of practical speech emotion,such aS ridgetiness,were analyzed.The pitch frequency,short-term energy,formant frequency and chaotic characteristics were analyzed corresponding to different emotion categories,and we constructed a 144-dimensional emotion feature vector for recognition and reduced to 4-dimension by adopting Linear Discriminant Analysis（LDA） Finally,the Im-SFLA-SVM method Was tested on the practical speech emotion database,and the recognition results were compared with Shuffled Frog Leaping Algorithm optimization-SVM（SFLA-SVM）method,Particle Swarm Optimization algorithm optimization-SVM（PSo-SVM） method,basic SVM,Gaussian Mixture Model（GMM）method and Back Propagation（BP）neural network method.The experimentM resuits showed that the average recognition rate of Im-SFLA-SVM method was 77.8%,which had improved 1.7%,2.7%,3.4%,4.7%and 7.8%respectively,compared with the other methods.The recognition of fidgetiness was significantly improve,thus verifying that Im-SFLA was an effective SVM parameter selection method,and the Im-SFLA-SVM method may significantly improve the practical speech emotion recognition.     

Robust algorithm of direction of arrival estimation for coherent wideband sources in unknown correlated noise fields

A robust algorithm of direction of arrival (DOA) estimation for coherent wideband sources in unknown correlated noise fields was investigated. The noise is usually unknown and correlated among sensors in practical applications, especially for arrays with comparatively small apertures. The spatially correlated noise incurs an increase in focusing error and a severe degradation in the DOA estimation, and therefore a method of focusing transformation based on differentiating covariance matrix was proposed to eliminate noise, hence reduce the focusing error. The simulation and experimental results demonstrate the effectiveness of the proposed method.     

A frequency bin-wise nonlinear masking algorithm in convolutive mixtures for speech segregation

A frequency bin-wise nonlinear masking algorithm is proposed in the spectrogram domain for speech segregation in convolutive mixtures. The contributive weight from each speech source to a time-frequency unit of the mixture spectrogram is estimated by a nonlinear function based on location cues. For each sound source, a non-binary mask is formed from the estimated weights and is multiplied to the mixture spectrogram to extract the sound. Head-related transfer functions (HRTFs) are used to simulate convolutive sound mixtures perceived by listeners. Simulation results show our proposed method outperforms convolutive independent component analysis and degenerate unmixing and estimation technique methods in almost all test conditions.     

Narrowband heterodyne reception using unstabilized sources

Source power for laboratory-type experiments is often limited at millimeter and submillimeter wavelengths. This requires the use of sensitive receiving equipment. Cooled square-law detectors and narrowband heterodyne detectors are examples. We have developed a coherent mechanical frequency shifter, which makes possible narrowband heterodyne detection without the need for highly frequency stable sources. Identical frequency and phase fluctuations of the transmit and local oscillator signals derived from one source are eliminated at the intermediate frequency. The widely tunable frequency shifter, designed for a 637GHz scale-model radar, was tested in a 140GHz non-radar configuration. We investigated the receiver's minimum coherently resolvable bandwidth and its sensitivity. Several types of sources were compared for the effect of local oscillator amplitude noise on receiver sensitivity at low intermediate frequency.     

A blind algorithm for reverberation-time estimation using subband decomposition of speech signals

An algorithm for blind estimation of reverberation time (RT) in speech signals is proposed. Analysis is restricted to the free-decaying regions of the signal, where the reverberation effect dominates, yielding a more accurate RT estimate at a reduced computational cost. A spectral decomposition is performed on the reverberant signal and partial RT estimates are determined in all signal subbands, providing more data to the statistical-analysis stage of the algorithm, which yields the final RT estimate. Algorithm performance is assessed using two distinct speech databases, achieving 91% and 97% correlation with the RTs measured by a standard nonblind method, indicating that the proposed method blindly estimates the RT in a reliable and consistent manner.     

A wavelet-based forward BSS algorithm for acoustic noise reduction and speech enhancement

In this paper, we address the problem of noise reduction and speech enhancement by adaptive filtering algorithm. Recently, the well known forward blind source separation (FBSS) structure has been largely studied and intensively used to reduce acoustic noise components and to enhance speech signal. The FBSS structure is often combined with adaptive algorithms to accelerate the adaptation of the cross-filters, and to improve noise suppression at the output. In this paper, we propose to use a wavelet transform decomposition in the FBSS structure by using a two-channel forward wavelet symmetric adaptive decorrelating (WFSAD) algorithm. The proposed WFSAD algorithm provides a better compromise between time and frequency resolution and improves robustness of the noise reduction process when compared with the classical two-channel forward symmetric adaptive decorrelating (FSAD) algorithm. Simulation results prove the efficiency of the proposed WFBSS algorithm in comparison with conventional ones in terms of several objective and subjective criteria.     

Narrowband phase sensitive fiber parametric amplifier

We describe a widely tunable phase sensitive fiber amplifier, based on narrowband parametric amplification in dispersion shifted fiber. Using a fiber with a zero dispersion wavelength of 1549?nm and a pump wavelength in the range of 1549?nm to 1532?nm, we obtained phase sensitive amplification between 1344?nm and 1781?nm, for an overall wavelength range of 437?nm. The amplifier threshold power is 7?W, and the maximum gain is 50?dB at a pump peak power of 25?W. The variance in gain due to phase sensitivity was measured to be up to 15?dB.     

A new regularized forward blind source separation algorithm for automatic speech quality enhancement

This paper addresses the problem of speech enhancement and acoustic noise reduction by adaptive filtering algorithms in a moving car through blind source separation (BSS) structures. In this paper we propose a new regularized forward blind source separation (RFBSS) algorithm that does not need voice activity detection (VAD) systems, and allows getting efficient speech enhancement performances with low complexity.