scholarly journals Performance on Speech Enhancement Objective Quality Measures Using Hybrid Wavelet Thresholding

2019 ◽  
Vol 8 (6) ◽  
pp. 3523-3533
Keyword(s):  
Speech Enhancement ◽  
Speech Signal ◽  
Quality Measures ◽  
Wavelet Thresholding ◽  
Wavelet Coefficients ◽  
Hard Thresholding ◽  
Improvement Set ◽  
Improvement Sets ◽  
Objective Quality

The quality of being easily understandable of the spe ech signals are very importantin communication and other speec h related systems. In order to improve these two in thespeech sign al, Speech improvement sets of computer instructions and devices are used so that itmay be better fully used by other speech proces sing setsof computer instructions. Most of the speech communica tion that requires atleast one microphone and the desired speech signal is usually contaminated by backgroundnoise and echo. As a result, the speech sign must be "cleaned" with advanced sign preparing devices before it is played out, transmitted, or put away. In this venture it has been investigated the required things and degree of upgrades in the field of discourse improvement utilizing discourse de-noising sets of PC directions announced in books with the fundamental intend to concentrate on the utilization of the window shape limits/rules in STSA based Speech Improvement process in which the sign destroyed by commotion is into edges and each part/segment is Windowed and the Windowed Speech pieces/parts zone connected to the Speech Improvement set of PC guidelines and the Improved Speech sign is modified in its time area. In general, the Speech Improvement methods make use theHam ming Window for this purpose. In this work an attempt has been made to study the effect of Window shape on the Speech. The Modified Improved thresholding is proposed by Asser Ghanbari and Mohammad Reza Karami and can be used like a hard thresholding limit with respect to the wavelet coefficients through and through worth progressively conspicuous than limit esteem and resembles an exponential capacity for the wavelet coefficients supreme worth not as much as edge esteem and is characterized.

Locally Adaptive Wavelet Thresholding for Speech Enhancement

2013 ◽  
Vol 380-384 ◽  
pp. 3618-3622
Author(s):  
Kang Liu ◽  
Jian Zheng Cheng ◽  
Li Cheng
Keyword(s):  
White Noise ◽  
Speech Enhancement ◽  
Speech Signal ◽  
Bayesian Framework ◽  
Threshold Function ◽  
Wavelet Thresholding ◽  
Wavelet Coefficients ◽  
Edge Preservation ◽  
Adaptive Wavelet ◽  
Locally Adaptive

There are strong dependencies between wavelet coefficients of speech signal,in this article,based on that,a new corresponding nonlinear threshold function derived in Bayesian framework is proposed to decrease the effect of the ambient noise.Analysis of the data shows the effectiveness of the proposed method that it removes white noise more effectually and gets better edge preservation.

scholarly journals BENCHMARKING THE OPTICAL RESOLVING POWER OF UAV BASED CAMERA SYSTEMS

2017 ◽  
Vol XLII-2/W6 ◽  
pp. 243-249 ◽  
Author(s):  
H. Meißner ◽  
M. Cramer ◽  
B. Piltz
Keyword(s):  
Quality Measures ◽  
Individual Performance ◽  
Imaging Systems ◽  
Resolving Power ◽  
Object Point ◽  
Geometric Calibration ◽  
Camera Systems ◽  
Objective Quality ◽  
Selection Of

UAV based imaging and 3D object point generation is an established technology. Some of the UAV users try to address (very) highaccuracy applications, i.e. inspection or monitoring scenarios. In order to guarantee such level of detail and accuracy high resolving imaging systems are mandatory. Furthermore, image quality considerably impacts photogrammetric processing, as the tie point transfer, mandatory for forming the block geometry, fully relies on the radiometric quality of images. Thus, empirical testing of radiometric camera performance is an important issue, in addition to standard (geometric) calibration, which normally is covered primarily. Within this paper the resolving power of ten different camera/lens installations has been investigated. Selected systems represent different camera classes, like DSLRs, system cameras, larger format cameras and proprietary systems. As the systems have been tested in wellcontrolled laboratory conditions and objective quality measures have been derived, individual performance can be compared directly, thus representing a first benchmark on radiometric performance of UAV cameras. The results have shown, that not only the selection of appropriate lens and camera body has an impact, in addition the image pre-processing, i.e. the use of a specific debayering method, significantly influences the final resolving power.

scholarly journals AUDIO SIGNALS CLIPPING DETECTION USING KURTOSIS AND ITS TRANSFORMS

2020 ◽  
pp. 411-417
Author(s):  
Arkadiy Prodeus ◽  
Maryna Didkovska
Keyword(s):  
Quality Measures ◽  
Subjective Assessment ◽  
Time Interval ◽  
Audio Signals ◽  
Relative Standard ◽  
Objective Quality ◽  
Music Signals ◽  
Musical Signals ◽  
Threshold Constant

This paper compares the results of subjective and objective assessments of the quality of speech and music signals distorted during clipping when large instantaneous signal values are replaced by a certain threshold constant or by values close to it. It was proposed in recent works to use kurtosis and some of its simple functional transforms such as reciprocal of kurtosis and square root of reciprocal of kurtosis as objective (instrumental) clipping value measures. This paper clarifies the results of a subjective assessment of the quality of speech and music signals distorted by clipping. A comparison of the obtained estimates allows one to conclude that the human auditory system is slightly more sensitive to the clipping of musical signals than to the clipping of speech signals, but this difference is small. Similarly, objective quality measures of clipped signals are almost equally sensitive to the clipping value of speech and music signals. An analysis of the variability of the kurtosis estimates, depending on the time of estimation, showed that the relative standard deviation of the kurtosis estimates is close to 10% for the analysis time interval of 1–40 s.

scholarly journals Wiener Filtering in Frequency Domain to Enhance Speech Corrupted by Colored Noise

2019 ◽  
Vol 8 (2S11) ◽  
pp. 1058-1062
Keyword(s):  
Frequency Domain ◽  
Performance Measures ◽  
Speech Enhancement ◽  
Colored Noise ◽  
Quality Measures ◽  
Wiener Filtering ◽  
Spectral Distortion ◽  
Gain Function ◽  
Objective Quality ◽  
Log Likelihood

This paper presents a method for speech enhancement to predict speech quality in presence of highly non-stationary scenarios using basic wiener filtering in frequency domain with an adaptive gain function under eight different noises at three different ranges of input SNR. Its performance is evaluated in terms of objective quality measures like LPC based spectral distortion measures are Cepstrum Distance, Itakura Saito and Log Likelihood Ratio. This method was tested using Noizeous database, its performance measures were compared against spectral subtractive type algorithms and it shows its improvements in terms of objective quality measures.

scholarly journals Point Cloud Coding Solutions, Subjective Assessment and Objective Measures: A Case Study

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 1955
Author(s):  
Emil Dumic ◽  
Luis A. da Silva Cruz
Keyword(s):  
Point Cloud ◽  
Point Clouds ◽  
Quality Measures ◽  
Subjective Assessment ◽  
Subjective Quality ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Objective Quality

This paper presents a summary of recent progress in compression, subjective assessment and objective quality measures of point cloud representations of three dimensional visual information. Different existing point cloud datasets, as well as discusses the protocols that have been proposed to evaluate the subjective quality of point cloud data. Several geometry and attribute point cloud data objective quality measures are also presented and described. A case study on the evaluation of subjective quality of point clouds in two laboratories is presented. Six original point clouds degraded with G-PCC and V-PCC point cloud compression and five degradation levels were subjectively evaluated, showing high inter-laboratory correlation. Furthermore, performance of several geometry-based objective quality measures applied to the same data are described, concluding that the highest correlation with subjective scores is obtained using point-to-plane measures. Finally, several current challenges and future research directions on point clouds compression and quality evaluation are discussed.

Speech Enhancement on Over-Complete Dictionary and Threshold Orthogonal Matching Pursuit

2014 ◽  
Vol 1044-1045 ◽  
pp. 1463-1468
Author(s):  
Xiao Cui ◽  
Wu Qing Zhang
Keyword(s):  
Discrete Cosine Transform ◽  
Speech Enhancement ◽  
Speech Signal ◽  
Matching Pursuit ◽  
Signal To Noise Ratio ◽  
Orthogonal Matching Pursuit ◽  
Cosine Transform ◽  
Perceptual Evaluation ◽  
Transform Coefficients

In order to suppress the noise, improve equipment's ability to further process information and improve the quality of voice, speech enhancement is often an important part of the speech signal preprocess. Contrastively analyze the characteristic that the clean speech signal coefficients in over-complete discrete cosine dictionary are much sparser than the traditional discrete cosine transform coefficients. Under noisy conditions, by setting the iterative threshold of orthogonal matching pursuit (OMP) algorithm, clean speech can be gotten, thus realize the speech enhancement. Simulation results of the signal waveform and spectrogram enhanced by the proposed algorithm are very similar to the original signal,comparative experiments also indicate that the signal to noise ratio (SNR) and the perceptual evaluation of speech quality (PESQ) score of the processed signal are superior to traditional discrete cosine transform (DCT).

scholarly journals A New Speech Enhancement Technique Based on Stationary Bionic Wavelet Transform and MMSE Estimate of Spectral Amplitude

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Mourad Talbi ◽  
Med Salim Bouhlel
Keyword(s):  
Wavelet Transform ◽  
Speech Enhancement ◽  
Hearing Aids ◽  
Speech Signal ◽  
Minimum Mean Square Error ◽  
Voice Conversion ◽  
Spectral Amplitude ◽  
Wavelet Coefficients ◽  
Enhancement Technique ◽  
Perceptual Evaluation

Speech enhancement has gained considerable attention in the employment of speech transmission via the communication channel, speaker identification, speech-based biometric systems, video conference, hearing aids, mobile phones, voice conversion, microphones, and so on. The background noise processing is needed for designing a successful speech enhancement system. In this work, a new speech enhancement technique based on Stationary Bionic Wavelet Transform (SBWT) and Minimum Mean Square Error (MMSE) Estimate of Spectral Amplitude is proposed. This technique consists at the first step in applying the SBWT to the noisy speech signal, in order to obtain eight noisy wavelet coefficients. The denoising of each of those coefficients is performed through the application of the denoising method based on MMSE Estimate of Spectral Amplitude. The SBWT inverse, S B W T − 1 , is applied to the obtained denoised stationary wavelet coefficients for finally obtaining the enhanced speech signal. The proposed technique’s performance is proved by the calculation of the Signal to Noise Ratio (SNR), the Segmental SNR (SSNR), and the Perceptual Evaluation of Speech Quality (PESQ).

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