Sub-band Main Peak Frequency Application for Speaker Identification

2011 ◽  
pp. 180-185
Author(s):  
Limin Hou ◽  
Juanmin Xie ◽  
Su Xie
Keyword(s):  
Speaker Identification ◽  
Peak Frequency ◽  
Main Peak

Acoustic behavior of Metaleptea adspersa (Orthoptera: Acrididae)

2002 ◽  
Vol 134 (1) ◽  
pp. 113-123 ◽  
Author(s):  
Estrellita Lorier ◽  
M. Dolores García ◽  
M. Eulalia Clemente ◽  
Juan José Presa
Keyword(s):  
Sound Production ◽  
Hind Wing ◽  
Peak Frequency ◽  
Tape Recorder ◽  
Main Peak ◽  
Acoustic Behavior ◽  
In Captivity

AbstractThe sounds produced by Metaleptea adspersa (Blanchard 1843) were recorded in captivity with an analogical tape recorder. The signal was digitized in the laboratory and studied with a software. Three types of sound were described: copulation, rivalry, and crepitation. All three sounds were produced only by males. The frequency of the sounds occupied a broadband, from 3–4 to 16 kHz, although the main peak frequency for each type of song differed. We also studied the structures involved in sound production. Copulation and rivalry songs were produced by the rubbing of the subcostal, radial, medial, and cubital 1 veins of the hind wing against the subcostal and radial veins of the tegmen; the enlarged cubital area of the hind wing acted as a resonator. Crepitation sound was produced by the cubital area of hind wing when its expanded membrane became taut.

scholarly journals Low β2 Main Peak Frequency in the Electroencephalogram Signs Vulnerability to Depression

2016 ◽  
Vol 10 ◽  
Author(s):  
Damien Claverie ◽  
Chrystel Becker ◽  
Antoine Ghestem ◽  
Mathieu Coutan ◽  
Françoise Camus ◽  
...  
Keyword(s):  
Peak Frequency ◽  
Main Peak

Numerical investigation of geometrical parameters on the hydrodynamic noise characteristics of submerged bodies and comparisons with experiments

2020 ◽  
pp. 147509022096224
Author(s):  
Sertaç Bulut ◽  
Selma Ergin
Keyword(s):  
Aspect Ratio ◽  
Peak Frequency ◽  
Broadband Noise ◽  
Circular Cylinders ◽  
Main Peak ◽  
Geometrical Parameters ◽  
Square Cylinder ◽  
Side Ratio ◽  
Cylinder Diameter ◽  
Hydroacoustic Measurements

The effects of the geometrical parameters on the hydroacoustic characteristics of the flow over rectangular, square and circular cylinders are investigated by numerical analyses and experiments. The numerical simulations are carried out by using a hybrid method which combines RANS with FWH equation. In order to validate the numerical results, the hydroacoustic measurements are also performed for the circular cylinders. The circular cylinders with diameters of 9.5, 19.0, 38.0 and 65.0 mm and aspect ratios of 2.5, 5.0 and 10.0 are employed for the hydroacoustic measurements and analyses. The rectangular cylinders with side ratios of 0.3, 0.6, 1.8 and 3.0, and also square cylinder with the side ratio of 1.0 are considered in hydroacoustic analyses. The Reynolds numbers are in the range of 2.25 × 104 and 1.7 × 105. The hydroacoustic characteristics of the cylinders are obtained to be completely different due to the differences in the shear layer separation, reattachment mechanism and the intensity of disturbance. The shape of the noise spectrum significantly changes with the geometrical shapes of the cylinders. The spectrum becomes narrower by an increase in the side ratio. The main peak frequency reduces when the side ratio increases. The highest value of the maximum sound pressure level, SPLmax are observed for the square cylinder and the lowest value for the rectangular cylinder with the side ratio of 0.6. The peak spectrum becomes like a line spectrum as the cylinder diameter decreases. The main peak frequency decreases when the cylinder diameter increases but it is almost constant with the aspect ratio. At the constant Reynolds number, the broadband noise level and SPLmax decrease with an increase in the cylinder diameter and decrease in the aspect ratio. A good agreement between the numerical and experimental results are obtained.

GAIT SPECTRAL ANALYSIS: AN EASY FAST QUANTITATIVE METHOD FOR DIAGNOSING PARKINSON'S DISEASE

2012 ◽  
Vol 12 (03) ◽  
pp. 1250041 ◽  
Author(s):  
YASHAR SARBAZ ◽  
FARZAD TOWHIDKHAH ◽  
SHAHRIAR GHARIBZADEH ◽  
AYYOOB JAFARI
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Clinical Data ◽  
Power Spectra ◽  
Final Diagnosis ◽  
Peak Frequency ◽  
Main Peak ◽  
Significant Difference ◽  
Frequency Components

At present, there is no quantitative test to definitely diagnose Parkinson's disease (PD). For this purpose, we computed the power spectra of stride and swing signals of normal persons and patients. The evaluation of power spectra in stride on normal group shows that the main peak of the frequency range is in the range of 0.018 to 0.02 Hz. In contrast, the main peak frequency is different in different PD patients. Our studies on swing signal and its power spectra show that there is a significant difference between the amplitude of frequency components between normal and PD groups. Patients show power spectra amplitude even more than 10 times that of normal patients. The clinical data were obtained from http://www.physionet.org. For measuring time intervals, force sensors were used in the plantar portion of the foot. Power spectra of left stride, right stride, and left swing were computed. Frequency domain of power spectra was divided into 10 parts and then the surface area under each part was calculated. We used artificial neural network for classification of these groups. The clinical data was divided into two parts, training and test sets. An accuracy of 93.75% was obtained during training. The test data was used for validation of the classifier and an accuracy of 92.86% was obtained. The proposed classifier may be used as a tool for helping the clinicians to diagnose PD. Surely the final diagnosis should be obtained by an expert neurologist.

Feature Extraction and Analysis of Passive Underwater Acoustic Signals for Different Species and Quantities of Freshwater Fish

2018 ◽  
Vol 61 (5) ◽  
pp. 1505-1513
Author(s):  
Qunzi Tu ◽  
Hanying Huang ◽  
Lu Li ◽  
Shanbai Xiong
Keyword(s):  
Feature Extraction ◽  
Power Spectrum ◽  
Frequency Band ◽  
Wavelet Packet ◽  
Peak Frequency ◽  
Main Peak ◽  
Wavelet Packet Decomposition ◽  
Band Energy ◽  
Frequency Band Energy ◽  
Peak Value

Abstract. The underwater signals from one and six breams, crucians, grass carps, and cyprinoids using a hydrophone were preprocessed by Wiener filtering. Three features were extracted: frequency band energy based on wavelet packet decomposition, average mel cepstral coefficient, and main peak frequency and main peak value based on the power spectrum. The effects of fish species and quantity on these features were analyzed. The results show that fish species had significant effects on the frequency band energy based on wavelet packet decomposition, average mel cepstral coefficient, and main peak frequency and main peak value based on the power spectrum. The fish quantity had significant effects on the frequency band energy based on wavelet packet decomposition and main peak value based on the power spectrum, but had no significant effects on the average mel cepstral coefficient and main peak frequency based on the power spectrum. Keywords: Feature extraction, Freshwater fish, Passive underwater acoustic technology, Significance analysis.

scholarly journals Frequency Downshifting in Wave Spectra in Coastal Zone and Its Influence on Mudbank Formation

2020 ◽  
Vol 8 (9) ◽  
pp. 723
Author(s):  
Yana Saprykina ◽  
Margarita Shtremel ◽  
Samiksha Volvaiker ◽  
Sergey Kuznetsov
Keyword(s):  
Wave Attenuation ◽  
Wind Waves ◽  
Wave Spectrum ◽  
Peak Frequency ◽  
Southwest Monsoon ◽  
Main Peak ◽  
Coastal Zones ◽  
Frequency Peak ◽  
The Difference ◽  
Frequency Downshifting

The evolution of wind waves in coastal zones leads to changes in the shape of the wave spectrum. Along the coast of Kerala, due to the presence of mudbanks during the southwest monsoon, we could observe downshifting of the peak frequency in the wave spectral data. The present study aims at proving the mechanism of frequency downshifting and possible influence of the downshifting process on mudbank formation. The results of SWASH (Simulating WAves till SHore) modeling and bispectral analysis shows that frequency downshifting occurs due to the difference nonlinear triad interactions of the main frequency peak of the wave spectrum with frequencies of the infragravity range independent of the viscosity of the medium. The increase in wave dissipation accelerates frequency downshifting additionally, decreasing the wave energy in the main peak frequency. It is shown that frequency downshifting can be one of the possible wave mechanisms of mudbank formation due to essentially different wave attenuation coefficients at the beginning and end of this process. For muddy cohesive sediments, it will lead to formation with an erosive profile at first and then an accumulative profile, i.e., mudbank formation.

Method for measuring distortions of a speech signal during its transmission over a communication channel to a biometric identification system

2020 ◽  
pp. 65-72
Author(s):  
V. V. Savchenko ◽  
A. V. Savchenko
Keyword(s):  
Speech Signal ◽  
Communication Channel ◽  
Speaker Identification ◽  
A Priori ◽  
Small Samples ◽  
Practical Implementation ◽  
Identification System ◽  
New Information ◽  
Discrimination Criterion ◽  
A Priori Uncertainty

This paper is devoted to the presence of distortions in a speech signal transmitted over a communication channel to a biometric system during voice-based remote identification. We propose to preliminary correct the frequency spectrum of the received signal based on the pre-distortion principle. Taking into account a priori uncertainty, a new information indicator of speech signal distortions and a method for measuring it in conditions of small samples of observations are proposed. An example of fast practical implementation of the method based on a parametric spectral analysis algorithm is considered. Experimental results of our approach are provided for three different versions of communication channel. It is shown that the usage of the proposed method makes it possible to transform the initially distorted speech signal into compliance on the registered voice template by using acceptable information discrimination criterion. It is demonstrated that our approach may be used in existing biometric systems and technologies of speaker identification.

Bilingual speaker identification: Chinese and English

2015 ◽  
Vol 22 (1) ◽  
pp. 57-78 ◽  
Author(s):  
Peggy P.K. Mok ◽  
Robert Bo Xu ◽  
Donghui Zuo
Keyword(s):  
Speaker Identification ◽  
Bilingual Speaker ◽  
Chinese And English
Sign in / Sign up

Export Citation Format

Share Document