Applied-Information Technology with Speech Enhancement Based on EMD and MF

2014 ◽  
Vol 1046 ◽  
pp. 384-387
Author(s):  
Jin Li ◽  
Kun Shen
Keyword(s):  
Information Technology ◽  
Speech Enhancement ◽  
Time Domain ◽  
Improved Method ◽  
Noisy Environments ◽  
Structuring Element ◽  
Mode Function ◽  
Mode Decomposition ◽  
Threshold Processing

Aiming at traditional methods cannot get good performance in noisy environments, an improved method for speech enhancement based on Empirical Mode Decomposition (EMD) and Morphology Filtering (MF) was proposed. The method firstly uses EMD to obtain Intrinsic Mode Function (IMF) and for hard threshold processing, then selects appropriate structuring element to construct MF for filtering processing in remaining IMFs. Finally, speech enhancement signal is reconstructed for each IMFs. Experimental results show that the proposed method for speech enhancement has better de-noising effect by comparing time-domain waveform and spectrogram. Moreover, the quality of reconstructed speech enhancement signal has been significantly improved.

scholarly journals Bolt Detection Signal Analysis Method Based on ICEEMD

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Chunhui Guo ◽  
Zhan Zhang ◽  
Xin Xie ◽  
Zhengyu Yang
Keyword(s):  
Signal Analysis ◽  
Approximate Entropy ◽  
Ensemble Empirical Mode Decomposition ◽  
Analysis Method ◽  
Détection Signal ◽  
Mode Function ◽  
Mode Decomposition ◽  
Signal Analysis Method ◽  
Detection Signal

The construction quality of the bolt is directly related to the safety of the project, and, as such, it must be tested. In this paper, the improved complete ensemble empirical mode decomposition (ICEEMD) method is introduced to the bolt detection signal analysis. The ICEEMD is used in order to decompose the anchor detection signal according to the approximate entropy of each intrinsic mode function (IMF). The noise of the IMFs is eliminated by the wavelet soft threshold denoising technique. Based on the approximate entropy and the wavelet denoising principle, the ICEEMD-De anchor signal analysis method is proposed. From the analysis of the vibration analog signal, as well as the bolt detection signal, the result shows that the ICEEMD-De method is capable of correctly separating the different IMFs under noisy conditions and also that the IMF can effectively identify the reflection signal of the end of the bolt.

scholarly journals Time-Domain Joint Training Strategies of Speech Enhancement and Intent Classification Neural Models

Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 374
Author(s):  
Mohamed Nabih Ali ◽  
Daniele Falavigna ◽  
Alessio Brutti
Keyword(s):  
Speech Enhancement ◽  
Time Domain ◽  
Background Noise ◽  
State Of The Art ◽  
Noisy Environments ◽  
Neural Models ◽  
Convolutional Network ◽  
Environmental Perturbations ◽  
Front End ◽  
The Time Domain

Robustness against background noise and reverberation is essential for many real-world speech-based applications. One way to achieve this robustness is to employ a speech enhancement front-end that, independently of the back-end, removes the environmental perturbations from the target speech signal. However, although the enhancement front-end typically increases the speech quality from an intelligibility perspective, it tends to introduce distortions which deteriorate the performance of subsequent processing modules. In this paper, we investigate strategies for jointly training neural models for both speech enhancement and the back-end, which optimize a combined loss function. In this way, the enhancement front-end is guided by the back-end to provide more effective enhancement. Differently from typical state-of-the-art approaches employing on spectral features or neural embeddings, we operate in the time domain, processing raw waveforms in both components. As application scenario we consider intent classification in noisy environments. In particular, the front-end speech enhancement module is based on Wave-U-Net while the intent classifier is implemented as a temporal convolutional network. Exhaustive experiments are reported on versions of the Fluent Speech Commands corpus contaminated with noises from the Microsoft Scalable Noisy Speech Dataset, shedding light and providing insight about the most promising training approaches.

scholarly journals Intelligent fault diagnosis of rotating machinery based on deep learning with feature selection

2019 ◽  
Vol 39 (4) ◽  
pp. 939-953 ◽  
Author(s):  
Dongying Han ◽  
Kai Liang ◽  
Peiming Shi
Keyword(s):  
Neural Network ◽  
Feature Selection ◽  
Deep Learning ◽  
Fault Diagnosis ◽  
Time Domain ◽  
Deep Neural Network ◽  
Intrinsic Mode Function ◽  
Mode Function ◽  
Mode Decomposition ◽  
Fault Features

In the absence of a priori knowledge, manual feature selection is too blind to find the sensitive features which can effectively classify the different fault features. And it is difficult to obtain a large number of typical fault samples in practice to train the intelligent classifier. A novel intelligent fault diagnosis method based on feature selection and deep learning is proposed for rotating machine mechanical in the paper. In this method, the deep neural network is not only used for feature extraction but also for fault diagnosis. First, the deep neural network 1 is used to extract feature from the spectral signal of the original signal. In addition, the original vibration signal is decomposed to a series of intrinsic mode function components by empirical mode decomposition, and the statistical features of each intrinsic mode function component are extracted by the deep neural network 2 in time domain and frequency domain. Second, the extraction features of the original signal spectrum and the extraction features of each intrinsic mode function component are evaluated, respectively. After features evaluation, the selected sensitive features are combined together to construct a joint feature. Finally, the joint feature is put into the deep neural network 3 to realize the automatic recognition of different fault states of rotating machinery. The experimental results show that the method proposed in this paper which integrated time-domain, frequency-domain statistical characteristics, empirical mode decomposition, feature selection, and deep learning methods can obtain the fault information in detail and can select sensitive features from a large number of fault features. The method can reduce the network size, improve the mechanical fault diagnosis classification accuracy, and has strong robustness.

scholarly journals Subband DCT and EMD Based Hybrid Soft Thresholding for Speech Enhancement

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Erhan Deger ◽  
Md. Khademul Islam Molla ◽  
Keikichi Hirose ◽  
Nobuaki Minematsu ◽  
Md. Kamrul Hasan
Keyword(s):  
Speech Enhancement ◽  
Time Domain ◽  
Noise Variance ◽  
Intrinsic Mode Functions ◽  
Soft Thresholding ◽  
Second Stage ◽  
Mode Decomposition ◽  
Dct Domain ◽  
Snr Improvement ◽  
Thresholding Algorithm

This paper presents a two-stage soft thresholding algorithm based on discrete cosine transform (DCT) and empirical mode decomposition (EMD). In the first stage, noisy speech is decomposed into eight frequency bands and a specific noise variance is calculated for each one. Based on this variance, each band is denoised using soft thresholding in DCT domain. The remaining noise is eliminated in the second stage through a time domain soft thresholding strategy adapted to the intrinsic mode functions (IMFs) derived by applying EMD on the signal obtained from the first stage processing. Significantly better SNR improvement and perceptual speech quality results for different noise types prove the superiority of the proposed algorithm over recently reported techniques.

Speech Enhancement Based on EMD and Wavelet Threshold in Noisy Environments

2014 ◽  
Vol 989-994 ◽  
pp. 3654-3657
Author(s):  
Zi Qin Chen ◽  
De Xiang Zhang ◽  
Da Ling Yuan
Keyword(s):  
Speech Enhancement ◽  
Speech Processing ◽  
Intrinsic Mode Functions ◽  
Noisy Environments ◽  
Mode Decomposition ◽  
Limited Function ◽  
Band Limited ◽  
A New Technique ◽  
Band Limited Function ◽  
Target Characteristics

Speech enhancement is crucial for speech recognition accuracy. How to eliminate the effect of the noise constitutes a challenging problem in speech processing. This paper presents a new technique for speech enhancement in a noisy environment based on the empirical mode decomposition (EMD) algorithm and wavelet threshold. With the EMD, the noise speech signals can be decomposed into a sum of the band-limited function called intrinsic mode functions (IMFs), which is a zero-mean AM-FM component. Then wavelet threshold of the IMF components can be used to eliminate the effect of the noise for speech enhancement. Experimental results show that the proposed speech enhancement by de-noising algorithm is possible to achieve an excellent balance between suppresses noise effectively and preserves as many target characteristics of original signal as possible.

Pengaruh Kualitas Sumber Daya Manusia, Pemanfaatan Teknologi Informasi, Dan Sistem Pengendalian Intern Terhadap Ketepatwaktuan Pelaporan Keuangan Pemerintah Desa

2018 ◽  
Vol 26 (2) ◽  
pp. 131-143
Author(s):  
Marlinawati Marlinawati ◽  
Dewi Kusuma Wardani
Keyword(s):  
Information Technology ◽  
Control System ◽  
Human Resources ◽  
Financial Reporting ◽  
Internal Control ◽  
Positive Influence ◽  
Internal Control System ◽  
Speed Up ◽  
Village Government

The purpose of this research is to know the influence between the Quality of Human Resources, Utilization of Information Technology and Internal Control System Against Timeliness of Village Government Financial Reporting at Gunungkidul Regency. This research is causative research. The population is the village government in Gunungkidul Regency, especially in Gedangsari subdistrict. Criteria of respondents in the study were to village and village apparatus. We use questionnaire to collect data. We use multiple regression with SPSS program version 16.0 to analyze data. We find that quality of human resources and internal control system have a positive influence on the timeliness of village government financial reporting. On the other hand, utilization of information technology does not influence the timeliness of village government financial reporting. These imply that the quality of human resources and internal control system can speed up the preparation of village government financial reporting.

JOINT INTERPRETATION OF AIRBORNE ELECTROMAGNETIC DATA IN THE TIME DOMAIN AND FREQUENCY DOMAIN

2018 ◽  
Vol 12 (7-8) ◽  
pp. 76-83
Author(s):  
E. V. KARSHAKOV ◽  
J. MOILANEN
Keyword(s):  
Fourier Transform ◽  
Frequency Domain ◽  
Time Domain ◽  
Frequency Interval ◽  
Single Spectrum ◽  
Simultaneous Inversion ◽  
Homogeneous Half Space ◽  
Time Domain Data ◽  
The Time Domain

Тhe advantage of combine processing of frequency domain and time domain data provided by the EQUATOR system is discussed. The heliborne complex has a towed transmitter, and, raised above it on the same cable a towed receiver. The excitation signal contains both pulsed and harmonic components. In fact, there are two independent transmitters operate in the system: one of them is a normal pulsed domain transmitter, with a half-sinusoidal pulse and a small "cut" on the falling edge, and the other one is a classical frequency domain transmitter at several specially selected frequencies. The received signal is first processed to a direct Fourier transform with high Q-factor detection at all significant frequencies. After that, in the spectral region, operations of converting the spectra of two sounding signals to a single spectrum of an ideal transmitter are performed. Than we do an inverse Fourier transform and return to the time domain. The detection of spectral components is done at a frequency band of several Hz, the receiver has the ability to perfectly suppress all sorts of extra-band noise. The detection bandwidth is several dozen times less the frequency interval between the harmonics, it turns out thatto achieve the same measurement quality of ground response without using out-of-band suppression you need several dozen times higher moment of airborne transmitting system. The data obtained from the model of a homogeneous half-space, a two-layered model, and a model of a horizontally layered medium is considered. A time-domain data makes it easier to detect a conductor in a relative insulator at greater depths. The data in the frequency domain gives more detailed information about subsurface. These conclusions are illustrated by the example of processing the survey data of the Republic of Rwanda in 2017. The simultaneous inversion of data in frequency domain and time domain can significantly improve the quality of interpretation.

Protection of Customers for Management of Digital Banking Services (Study at PT. BRI Unit Boyolali)

2020 ◽  
Vol 3 (2) ◽  
pp. 170
Author(s):  
Herdian Ayu Andreana Beru Tarigan ◽  
Darminto Hartono Paulus
Keyword(s):  
Information Technology ◽  
Financial Services ◽  
Banking Industry ◽  
Service Innovation ◽  
Quality Of Services ◽  
Legal Research ◽  
Banking Services ◽  
Services Sector ◽  
Financial Services Sector

<p>Increasing competition in the Indonesian banking industry has encouraged many banks to improve the quality of services to customers by utilizing information technology developments. Service innovation in the use of information technology encourages banks to enter the era of digital banking services. However, the development of digital banking services also increases the risks faced by banks. The purpose of this study is to provide an overview of the implementation of digital banking services and customer protection for risks from digital banking services. The method used in this study is an empirical legal research method. The results of this study indicate that the implementation of digital banking services is regulated by OJK Regulation No.12/POJK.03/2018. The existence of this OJK Regulation is expected by banks as providers of digital banking services to always prioritize risk management in the use of information technology. In addition, this study also shows the existence of 2 types of customer protection for the use of digital banking services, namely preventive protection in the form of legislation related to customer protection in the financial services sector and repressive protection in the form of bank accountability for complaints from customers using digital banking services.</p>

KAJIAN LITERATUR MODEL KONSEPTUAL KEBERHASILAN E-GOVERNMENT

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Bernadus Gunawan Sudarsono ◽  
Sri Poedji Lestari
Keyword(s):  
Information Technology ◽  
Best Practice ◽  
Public Services ◽  
Developed Countries ◽  
Internet Technology ◽  
Electronic Government ◽  
Digital Government ◽  
Management Ethics ◽  
The Government

The use of internet technology in the government environment is known as electronic government or e-government. In simple terms, e-government or digital government is an activity carried out by the government by using information technology support in providing services to the community. In line with the spirit of bureaucratic reform in Indonesia, e-government has a role in improving the quality of public services and helping the process of delivering information more effectively to the public. Over time, the application of e-Government has turned out to have mixed results. In developed countries, the application of e-Government systems in the scope of government has produced various benefits ranging from the efficiency of administrative processes and various innovations in the field of public services. But on the contrary in the case of developing countries including Indonesia, the results are more alarming where many government institutions face obstacles and even fail to achieve significant improvements in the quality of public services despite having adequate information and communication technology. The paradigm of bureaucrats who wrongly considers that the success of e-Government is mainly determined by technology. Even though there are many factors outside of technology that are more dominant as causes of failure such as organizational management, ethics and work culture. This study aims to develop a model of success in the application of e-Government from several best practice models in the field of information technology that have been widely used so far using literature studies as research methods. The results of the study show that the conceptual model of the success of the implementation of e-Government developed consists of 17 determinants of success..Keywords: Model, Factor, Success, System, e-Government

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