特音按摩法在运动中的运用

不同特音对机体影响及作用的部位不同，在与按摩手法结合时应有针对性的选用。

新疆尼勒克县加勒格斯哈音特和铁木里克沟口墓地考古发掘成果简述

加勒格斯哈音特墓地和铁木里克沟口墓地是吉林台古墓群中的两处重要墓地.吉林台墓群位于新疆伊犁河上游支流喀什河上游两岸台地上.喀什河河水丰足,河两岸山前台地上植被茂盛,这里很早就是游牧民族生息繁衍的地方.

Support vector machines for emotion recognition in Chinese speech

Support vector machines (SVMs) are utilized for emotion recognition in Chinese speech in this paper. Both binary class discrimination and the multi class discrimination are discussed. It proves that the emotional features construct a nonlinear problem in the input space, and SVMs based on nonlinear mapping can solve it more effectively than other linear methods. Multi class classification based on SVMs with a soft decision function is constructed to classify the four emotion situations. Compared with principal component analysis (PCA) method and modified PCA method, SVMs perform the best result in multi class discrimination by using nonlinear kernel mapping.

Principal Component Feature for ANN-Based Speech Recognition

Using function approximation technology and principal component analysis method, this paper presents a principal component feature to solve the time alignment problem and to simplify the structure of neural network. Its extraction simulates the processing of speech information in human auditory system. The experimental results show that the principal component feature based recognition system outperforms the standard CDHMM and GMDS method in many aspects.

Speech emotion recognition using semi-supervised discriminant analysis

Semi-supervised discriminant analysis SDA which uses a combination of multiple embedding graphs and kernel SDA KSDA are adopted in supervised speech emotion recognition.When the emotional factors of speech signal samples are preprocessed different categories of features including pitch zero-cross rate energy durance formant and Mel frequency cepstrum coefficient MFCC as well as their statistical parameters are extracted from the utterances of samples.In the dimensionality reduction stage before the feature vectors are sent into classifiers parameter-optimized SDA and KSDA are performed to reduce dimensionality.Experiments on the Berlin speech emotion database show that SDA for supervised speech emotion recognition outperforms some other state-of-the-art dimensionality reduction methods based on spectral graph learning such as linear discriminant analysis LDA locality preserving projections LPP marginal Fisher analysis MFA etc. when multi-class support vector machine SVM classifiers are used.Additionally KSDA can achieve better recognition performance based on kernelized data mapping compared with the above methods including SDA.

Comparative Study on VQ-Based Efficient Mandarin Speech Recognition Method

A VQ based efficient speech recognition method is introduced, and the key parameters of this method are comparatively studied. This method is especially designed for mandarin speaker dependent small size word set recognition. It has less complexity, less resource consumption but higher ARR (accurate recognition rate) compared with traditional HMM or NN approach. A large scale test on the task of 11 mandarin digits recognition shows that the WER(word error rate) can reach 3 86%. This method is suitable for being embedded in PDA (personal digital assistant), mobile phone and so on to perform voice controlling like digits dialing, name dialing, calculating, voice commanding, etc.

Finite Element Simulation of the Vibratory Characteristics for Quartz Tuning Fork Gyroscope

The micro quartz crystal tuning fork gyroscope is a new type of vibratory gyroscope. The gyroscope should be analyzed and simulated early in the design stage in order to offer reliable basis for design and to shorten the period of development. Thus the vibratory characteristics of the gyroscope is simulated with the finite element method of coupled field. The optimum exciting frequency and the factors which influence the gyroscope sensitivity are determined. The method for adjusting the frequency deviation between driving and detecting modes is also proposed.

海口市人民政府关于发布《海口市盘活房地产市场若干办法》的通知

各区人民政府、市政府直属各单位: (海口市盘活房地产市场若干办法)已经市政府第十二次常务会议审议通过,现予发布施行。 一九九八年十二月十八日 海口市盘活房地产市场若干办法 为了启动消费市场,盘活存量房地产,促进我市房地产业持续健康发展,制定本办法。

Novel feature fusion method for speech emotion recognition based on multiple kernel learning

In order to improve the performance of speech emotion recognition, a novel feature fusion method is proposed. Based on the global features, the local information of different kinds of features is utilized. Both the global and the local features are combined together. Moreover, the multiple kernel learning method is adopted. The global features and each kind of local feature are respectively associated with a kernel, and all these kernels are added together with different weights to obtain a mixed kernel for nonlinear mapping. In the reproducing kernel Hilbert space, different kinds of emotional features can be easily classified. In the experiments, the popular Berlin dataset is used, and the optimal parameters of the global and the local kernels are determined by cross-validation. After computing using multiple kernel learning, the weights of all the kernels are obtained, which shows that the formant and intensity features play a key role in speech emotion recognition. The classification results show that the recognition rate is 78. 74% by using the global kernel, and it is 81.10% by using the proposed method, which demonstrates the effectiveness of the proposed method.

Pathological Voice Classification Based on Features Dimension Opti mization

The classification of pathological voice from healthy voice was studied based upon 27 acoustic features derived from a single sound signal of vowel /a:/. First, the feature space was transferred to reduce the data dimension by principle component analysis (PCA). Then the voice samples were classified according to the reduced PCA parameters by support vector machine (SVM) using radial basis function (RBF) as a kernel function. Meanwhile, by changing the ratio of opposite class samples, the accuracy under different features combinations was tested. Experimental data were provided by the voice database of Massachusetts Eye and Ear Infirmary (MEEI) in which 216 vowel /a:/ samples were collected from subjects of healthy and pathological cases, and tested with 5 fold cross-validation method. The result shows the positive rate of pathological voices was improved from 92% to 98% through the PCA method. STD, Fatr, Tasm, NHR, SEG, and PER are pathology sensitive features in illness detection. Using these sensitive features the accuracy of detection of pathological voice from healthy voice can reach 97%.

Experimental Research on the Double-peak Characteristic of Underwater Radiated Noise in the Near Field on Top of a Submarine

The double-peak characteristic of underwater radiated noise in the near field on top of the target submarine was analyzed in depth on the basis of submarine test data on the sea. The contribution of three major noise sources to the radiated noise of a submarine were compared and analyzed, and emphasis was put on the original source, production mechanism, and their correlative characteristics. On the basis of analysis on underwater tracking and pass through characteristics of the target submarine, the double-peak phenomenon was reasonably interpreted. Furthermore, the correctness of the theoretical interpretation was verified adequately in real submarine tests. The double-peak phenomenon indicates that the space distributing character on submarine radiated noise are both asymmetrical with time and space, whereas that is provided with directivity. Studying the double-peak phenomenon in depth has important reference value and meaning in engineering practice for understanding the underwater radiated noise field of submarines.

Frame-bitrate-change based steganography for voice-over-IP

Steganography based on bits-modification of speech frames is a kind of commonly used method, which targets at RTP payloads and offers covert communications over voice-over-IP(Vo IP). However, direct modification on frames is often independent of the inherent speech features, which may lead to great degradation of speech quality. A novel frame-bitrate-change based steganography is proposed in this work, which discovers a novel covert channel for Vo IP and introduces less distortion. This method exploits the feature of multi-rate speech codecs that the practical bitrate of speech frame is identified only by speech decoder at receiving end. Based on this characteristic, two steganography strategies called bitrate downgrading(BD) and bitrate switching(BS)are provided. The first strategy substitutes high bit-rate speech frames with lower ones to embed secret message, which introduces very low distortion in practice, and much less than other bits-modification based methods with the same embedding capacity. The second one encodes secret message bits into different types of speech frames, which is an alternative choice for supplement. The two strategies are implemented and tested on our covert communication system Steg Vo IP. The experiment results show that our proposed method is effective and fulfills the real-time requirement of Vo IP communication.

Spectral analysis of bowel sounds in intestinal obstruction using an electronic stethoscope

AIM: To determine the value of bowel sounds analysis using an electronic stethoscope to support a clinical diagnosis of intestinal obstruction. METHODS: Subjects were patients who presented with a diagnosis of possible intestinal obstruction based on symptoms, signs, and radiological findings. A 3MTH Littmann Model 4100 electronic stethoscope was used in this study. With the patients lying supine, six 8-second recordings of bowel sounds were taken from each patient from the lower abdomen. The recordings were analysed for sound duration, soundto-sound interval, dominant frequency, and peak frequency. Clinical and radiological data were reviewed and the patients were classified as having either acute, subacute, or no bowel obstruction. Comparison of bowel sound characteristics was made between these subgroups of patients. In the presence of an obstruction, the site of obstruction was identified and bowel calibre was also measured to correlate with bowel sounds. RESULTS: A total of 71 patients were studied during the period July 2009 to January 2011. Forty patientshad acute bowel obstruction (27 small bowel obstruction and 13 large bowel obstruction), 11 had subacute bowel obstruction (eight in the small bowel and three in large bowel) and 20 had no bowel obstruction (diagnoses of other conditions were made). Twenty-five patients received surgical intervention (35.2%) during the same admission for acute abdominal conditions. A total of 426 recordings were made and 420 recordings were used for analysis. There was no significant difference in sound-to-sound interval, dominant frequency, and peak frequency among patients with acute bowel obstruction, subacute bowel obstruction, and no bowel obstruction. In acute large bowel obstruction, the sound duration was significantly longer (median 0.81 s vs 0.55 s, P = 0.021) and the dominant frequency was significantly higher (median 440 Hz vs 288 Hz, P = 0.003) when compared to acute small bowel obstruction. No significant difference was seen between acute large bowel obstruction and large bowel pseudoobstruction. For patients with small bowel obstruction, the sound-to-sound interval was significantly longer in those who subsequently underwent surgery compared with those treated non-operatively (median 1.29 s vs 0.63 s, P < 0.001). There was no correlation between bowel calibre and bowel sound characteristics in both acute small bowel obstruction and acute large bowel obstruction. CONCLUSION: Auscultation of bowel sounds is nonspecific for diagnosing bowel obstruction. Differences in sound characteristics between large bowel and small bowel obstruction may help determine the likely site of obstruction.

Feature-preserving mesh denoising based on contextual discontinuities

Motivated by the conception of Lee et al.(2005)’s mesh saliency and Chen (2005)’s contextual discontinuities, a novel adaptive smoothing approach is proposed for noise removal and feature preservation. Mesh saliency is employed as a multiscale measure to detect contextual discontinuity for feature preserving and control of the smoothing speed. The proposed method is similar to the bilateral filter method. Comparative results demonstrate the simplicity and efficiency of the presented method, which makes it an excellent solution for smoothing 3D noisy meshes.

Noise Temperature Characteristics and Gain-control of Avalanche Photodiodes for Laser Radar

Avalanche photodiodes(APDs) are promising light sensors with high quantum efficiency and low noise. It has been extensively used in radiation detection,laser radar and other weak signal detection fields. Unlike other photodiodes,APD is a very sensitive light detector with very high internal gain. The basic theory shows that the gain of APD is related to the temperature. The internal gain fluctuates with the variation of temperature. Investigated was the influence of the variation of the gain induced by the fluctuation of temperature on the output from APD for a very weak laser pulse input in laser radar. An active reverse-biased voltage compensation method is used to stabilize the gain of APD. An APD model is setup to simulate the detection of light pulse signal. The avalanche process,various noises and temperature's effect are all included in the model. Our results show that for the detection of weak light signal such as in laser radar,even a very small fluctuation of temperature could cause a great effect on APD's gain. The results show that the signal-to-noise ratio of the APD's output could be improved effectively with the active gain-control system.

Analysis on the Characteristics of Singing Liao Songs with Male Voice in Pingguo of Guangxi

Liao songs are the cultural and artistic products brewed by the people of Zhuang ethnic minority for thousand years. In this paper, the style and characteristics of singing Zhuang ethnic minority＇s Liao songs with male＇s two-part voice in Guangxi are mainly introduced through an analysis of vocal music and the study on the performance forms, singing language characteristics, and vocal music and resonance is mainly included, and also the important significance of singing Zhuang ethnic minority＇s Liao songs with male＇s two-part voice is discussed. Also, it is compared with the modern Chinese folk singing styles.

Saudi Speakers＇ Perception of the English Bilabial Stops/b/and/p/

Languages differ in their phoneme inventories. Some phonemes exist in more than one language but others exist in relatively few languages. More specifically, English Language has some sounds that Arabic does not have and vice versa. This paper focuses on the perception of the English bilabial stops/b/and/p/in contrast to the perception of the English alveolar stops/t/and/d/by some Saudi linguists who have been speaking English for more than six years and who are currently in an English speaking country, Australia. This phenomenon of perception of the English bilabial stops/b/and/p/will be tested mainly by virtue of minimal pairs and other words that may better help to investigate this perception. The paper uses some minimal pairs in which the bilabial and alveolar stops occur initially and finally. Also, it uses some verbs that end with the suffix/-ed/, but this/-ed/suffix is pronounced [t] or [d] when preceded by /p/ or /b/ respectively. Notice that [t] and [d] are allophones of the English past tense morpheme/-ed/（for example, Fromkin, Rodman, ＆ Hyams, 2007）. The pronunciation of the suffix as It] and [d] works as a clue for the subjects to know the preceding bilabial sound.

STATISTICAL FEATURE OF PITCH FREQUENCY DISTRIBUTIONS FOR OBUST SPEAKER IDENTIFICATION

This letter proposes an effective and robust speech feature extraction method based on statistical analysis of Pitch Frequency Distributions (PFD) for speaker identification. Compared with the conventional cepstrum, PFD is relatively insensitive to Additive White Gaussian Noise (AWGN), but it does not show good performance for speaker identification, even if under clean environments. To compensate this shortcoming, PFD and conventional cepstrum are combined to make the ultimate decision, instead of simply taking one kind of features into account.Experimental results indicate that the hybrid approach can give outstanding improvement for text-independent speaker identification under noisy environments corrupted by AWGN.

Enhancement of Voice Quality and Bit-rate Reduction by Prosodic Control in G.723.1 Vocoder

Speech coding techniques have been studied not truly to reduce the complexity and bit rate but also to improve the sound quality. CELP type vocoder, used as standard, supports the great stead quality even low bit rate. In this paper, the preprocessing of input speech to reduce the bit rate is different from the conventional vocoder. Different kinds of parameter are used for the preprocessing compared with the other parameters to t＇md the more appropriate parameter for the vocoder. The Parameters are used to synthesize the speech not to encode or decode for coding technique so we proposed the simple algorithm not to have the influence on the processing time or the computation time. The parameters in the preprocessing step are speaking rate, duration, and PSOLA technique.

A document-level model for tweet event detection

Social media like Twitter who serves as a novel news medium and has become increasingly popular since its establishment. Large scale first-hand user-generated tweets motivate automatic event detection on Twitter. Previous unsupervised approaches detected events by clustering words. These methods detect events using burstiness,which measures surging frequencies of words at certain time windows. However,event clusters represented by a set of individual words are difficult to understand. This issue is addressed by building a document-level event detection model that directly calculates the burstiness of tweets,leveraging distributed word representations for modeling semantic information,thereby avoiding sparsity. Results show that the document-level model not only offers event summaries that are directly human-readable,but also gives significantly improved accuracies compared to previous methods on unsupervised tweet event detection,which are based on words/segments.