Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "wavelet transform" wg kryterium: Temat

  Lista filtrów
Wyrównaj
    Wyświetlanie 1-12 z 12
    Tytuł:
    Phoneme Segmentation Based on Wavelet Spectra Analysis
    Autorzy:
    Ziółko, B.
    Manandhar, S.
    Wilson, R. C.
    Ziółko, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/177480.pdf
    Data publikacji:
    2011
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    speech recognition
    speech segmentation
    discrete wavelet transform
    Opis:
    A phoneme segmentation method based on the analysis of discrete wavelet transform spectra is described. The localization of phoneme boundaries is particularly useful in speech recognition. It enables one to use more accurate acoustic models since the length of phonemes provide more information for parametrization. Our method relies on the values of power envelopes and their first derivatives for six frequency subbands. Specific scenarios that are typical for phoneme boundaries are searched for. Discrete times with such events are noted and graded using a distribution-like event function, which represent the change of the energy distribution in the frequency domain. The exact definition of this method is described in the paper. The final decision on localization of boundaries is taken by analysis of the event function. Boundaries are, therefore, extracted using information from all subbands. The method was developed on a small set of Polish hand segmented words and tested on another large corpus containing 16 425 utterances. A recall and precision measure specifically designed to measure the quality of speech segmentation was adapted by using fuzzy sets. From this, results with F-score equal to 72.49% were obtained.
    Źródło:
    Archives of Acoustics; 2011, 36, 1; 29-47
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Phase Autocorrelation Bark Wavelet Transform (PACWT) Features for Robust Speech Recognition
    Autorzy:
    Majeed, S. A.
    Husain, H.
    Samad, S. A.
    Powiązania:
    https://bibliotekanauki.pl/articles/177326.pdf
    Data publikacji:
    2015
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    speech recognition
    feature extraction
    phase autocorrelation
    wavelet transform
    Opis:
    In this paper, a new feature-extraction method is proposed to achieve robustness of speech recognition systems. This method combines the benefits of phase autocorrelation (PAC) with bark wavelet transform. PAC uses the angle to measure correlation instead of the traditional autocorrelation measure, whereas the bark wavelet transform is a special type of wavelet transform that is particularly designed for speech signals. The extracted features from this combined method are called phase autocorrelation bark wavelet transform (PACWT) features. The speech recognition performance of the PACWT features is evaluated and compared to the conventional feature extraction method mel frequency cepstrum coefficients (MFCC) using TI-Digits database under different types of noise and noise levels. This database has been divided into male and female data. The result shows that the word recognition rate using the PACWT features for noisy male data (white noise at 0 dB SNR) is 60%, whereas it is 41.35% for the MFCC features under identical conditions.
    Źródło:
    Archives of Acoustics; 2015, 40, 1; 25-31
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Acoustical Analysis of Enclosure as Initial Approach to Vehicle Induced Noise Analysis Comparatevely Using STFT and Wavelets
    Autorzy:
    Błażejewski, A.
    Kozioł, P.
    Łuczak, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/176551.pdf
    Data publikacji:
    2014
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    modal analysis
    short-time Fourier transform
    wavelet transform
    acoustic signal processing
    Opis:
    It is assumed in the paper that the signals in the enclosure in a transient period are similar to a noise induced by vehicles, tracks, cars, etc. passing by. The components of such signals usually points out specific dynamic processes running during the observation or measurements. In order to choose the best method of analysis of these phenomena, an acoustic field in a closed space with a sound source inside is created. Acoustic modes of this space influence the sound field. Analytically, the modal analyses describe the above mentioned phenomena. The experimental measurements were conducted in the room that might comprise the closed space with known boundary conditions and the sound source Br¨uel & Kjær Omni-directional type 4292 inside. To record sound signals before the field’s steady state was reached, the microphone type 4349 and the 4-channel frontend 3590 had been used. The obtained signals have been analysed by using two approaches, i.e. Fourier and the wavelet analysis, with the emphasis on their efficiency and the capability to recognise important details of the signal. The results obtained for the enclosure might lead to the formulation of a methodology for an extended investigation of a rail track or vehicles dynamics.
    Źródło:
    Archives of Acoustics; 2014, 39, 3; 385-394
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A Lifting Wavelet Domain Audio Watermarking Algorithm Based on the Statistical Characteristics of Sub-Band Coefficients
    Autorzy:
    Tao, Z.
    Zhao, H.
    Wu, J.
    Gu, J.
    Xu, Y.
    Wu, D.
    Powiązania:
    https://bibliotekanauki.pl/articles/177956.pdf
    Data publikacji:
    2010
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    audio watermarking
    lifting wavelet transform
    statistical characteristics
    sub-band coefficients
    Opis:
    In this paper, a new lifting wavelet domain audio watermarking algorithm based on the statistical characteristics of sub-band coefficients is proposed. First of all, an original audio signal was segmented and each segment was divided into two sections. Then, the Barker code was used for synchronization, the LWT (lifting wavelet transform) was performed on each section, a synchronization code and a watermark were embedded into the first section and the second section, respectively, by modifying the statistical average value of the sub-band coefficients. The embed strength was determined adaptively according to the auditory masking property. Experiments show that the embedded watermark has better robustness against common signal processing attacks than present algorithms based on LWT and can resist random cropping in particular.
    Źródło:
    Archives of Acoustics; 2010, 35, 4; 481-491
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Application of Acoustic Signals for Rectifier Fault Detection in Brushless Synchronous Generator
    Autorzy:
    Rahnama, Mehdi
    Vahedi, Abolfazl
    Powiązania:
    https://bibliotekanauki.pl/articles/177304.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    acoustic emission
    wavelet transform
    K-Nearest Neighbours
    fault detection
    brushless generator
    Opis:
    One of the most important issues that power companies face when trying to reduce time and cost maintenance is condition monitoring. In electricity market worldwide, a significant amount of electrical energy is produced by synchronous machines. One type of these machines is brushless synchronous generators in which the rectifier bridge is mounted on rotating shafts. Since bridge terminals are not accessible in this type of generators, it is difficult to detect the possible faults on the rectifier bridge. Therefore, in this paper, a method is proposed to facilitate the rectifier fault detection. The proposed method is then evaluated by applying two conventional kinds of faults on rectifier bridges including one diode open-circuit and two diode open-circuit (one phase open-circuit of the armature winding in the auxiliary generator in experimental set). To extract suitable features for fault detection, the wavelet transform has been used on recorded audio signals. For classifying faulty and healthy states, K-Nearest Neighbours (KNN) supervised classification method was used. The results show a good accuracy of the proposed method.
    Źródło:
    Archives of Acoustics; 2019, 44, 2; 267-276
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Speech Enhancement Based on the Multi-Scales and Multi-Thresholds of the Auditory Perception Wavelet Transform
    Autorzy:
    Tao, Z.
    Zhao, H. M.
    Zhang, X-J.
    Wu, D.
    Powiązania:
    https://bibliotekanauki.pl/articles/177021.pdf
    Data publikacji:
    2011
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    speech enhancement
    low SNR
    auditory perception wavelet transform
    unvoiced enhancement
    masking effect
    Opis:
    This paper proposes a speech enhancement method using the multi-scales and multi-thresholds of the auditory perception wavelet transform, which is suitable for a low SNR (signal to noise ratio) environment. This method achieves the goal of noise reduction according to the threshold processing of the human ear’s auditory masking effect on the auditory perception wavelet transform parameters of a speech signal. At the same time, in order to prevent high frequency loss during the process of noise suppression, we first make a voicing decision based on the speech signals. Afterwards, we process the unvoiced sound segment and the voiced sound segment according to the different thresholds and different judgments. Lastly, we perform objective and subjective tests on the enhanced speech. The results show that, compared to other spectral subtractions, our method keeps the components of unvoiced sound intact, while it suppresses the residual noise and the background noise. Thus, the enhanced speech has better clarity and intelligibility.
    Źródło:
    Archives of Acoustics; 2011, 36, 3; 519-532
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Sleep Snoring Sound Recognition Based on Wavelet Packet Transform
    Autorzy:
    Ding, Li
    Peng, Jianxin
    Zhang, Xiaowen
    Song, Lijuan
    Powiązania:
    https://bibliotekanauki.pl/articles/31339924.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    snoring recognition
    wavelet packet transform
    feature selection
    machine learning
    Opis:
    Snoring is a typical and intuitive symptom of the obstructive sleep apnea hypopnea syndrome (OSAHS), which is a kind of sleep-related respiratory disorder having adverse effects on people’s lives. Detecting snoring sounds from the whole night recorded sounds is the first but the most important step for the snoring analysis of OSAHS. An automatic snoring detection system based on the wavelet packet transform (WPT) with an eXtreme Gradient Boosting (XGBoost) classifier is proposed in the paper, which recognizes snoring sounds from the enhanced episodes by the generalization subspace noise reduction algorithm. The feature selection technology based on correlation analysis is applied to select the most discriminative WPT features. The selected features yield a high sensitivity of 97.27% and a precision of 96.48% on the test set. The recognition performance demonstrates that WPT is effective in the analysis of snoring and non-snoring sounds, and the difference is exhibited much more comprehensively by sub-bands with smaller frequency ranges. The distribution of snoring sound is mainly on the middle and low frequency parts, there is also evident difference between snoring and non-snoring sounds on the high frequency part.
    Źródło:
    Archives of Acoustics; 2023, 48, 1; 3-12
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Development of a Sound Quality Evaluation Model Based on an Optimal Analytic Wavelet Transform and an Artificial Neural Network
    Autorzy:
    Pourseiedrezaei, Mehdi
    Loghmani, Ali
    Keshmiri, Mehdi
    Powiązania:
    https://bibliotekanauki.pl/articles/1953511.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    analytic wavelet transform
    AWT
    sound quality evaluation
    SQE
    psychoacoustic metrics
    back propagation neural network
    BPNN
    Opis:
    The purpose of this study was to develop a sound quality model for real time active sound quality control systems. The model is based on an optimal analytic wavelet transform (OAWT) used along with a back propagation neural network (BPNN) in which the initial weights and thresholds are determined by particle swarm optimisation (PSO). In the model the input signal is decomposed into 24 critical bands to extract a feature matrix, based on energy, mean, and standard deviation indices of the sub signal scalogram obtained by OAWT. The feature matrix is fed into the neural network input to determine the psychoacoustic parameters used for sound quality evaluation. The results of the study show that the present model is in good agreement with psychoacoustic models of sound quality metrics and enables evaluation of the quality of sound at a lower computational cost than the existing models.
    Źródło:
    Archives of Acoustics; 2021, 46, 1; 55-65
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Speech Enhancement Based on Discrete Wavelet Packet Transform and Itakura-Saito Nonnegative Matrix Factorisation
    Autorzy:
    Liu, Houguang
    Wang, Wenbo
    Xue, Lin
    Yang, Jianhua
    Wang, Zhihua
    Hua, Chunli
    Powiązania:
    https://bibliotekanauki.pl/articles/1448505.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    speech enhancement
    discrete wavelet packet transform
    nonnegative matrix factorisation
    Itakura-Saito divergence
    Opis:
    Nonnegative matrix factorization (NMF) is one of the most popular machine learning tools for speech enhancement (SE). However, there are two problems reducing the performance of the traditional NMF-based SE algorithms. One is related to the overlap-and-add operation used in the short time Fourier transform (STFT) based signal reconstruction, and the other is the Euclidean distance used commonly as an objective function; these methods can cause distortion in the SE process. In order to get over these shortcomings, we propose a novel SE joint framework which combines the discrete wavelet packet transform (DWPT) and the Itakura-Saito nonnegative matrix factorisation (ISNMF). In this approach, the speech signal was first split into a series of subband signals using the DWPT. Then, the ISNMF was used to enhance the speech for each subband signal. Finally, the inverse DWPT (IDWT) was utilised to reconstruct these enhanced speech subband signals. The experimental results show that the proposed joint framework effectively enhances the performance of speech enhancement and performs better in the unseen noise case compared to the traditional NMF methods.
    Źródło:
    Archives of Acoustics; 2020, 45, 4; 565-572
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Prediction of Psychoacoustic Metrics Using Combination of Wavelet Packet Transform and an Optimized Artificial Neural Network
    Autorzy:
    Pourseiedrezaei, Mehdi
    Loghmani, Ali
    Keshmiri, Mehdi
    Powiązania:
    https://bibliotekanauki.pl/articles/177762.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    sound quality measurement
    psychoacoustic metrics
    wavelet packet transform
    optimized artificial neural network
    Opis:
    In this paper, a modified sound quality evaluation (SQE) model is developed based on combination of an optimized artificial neural network (ANN) and the wavelet packet transform (WPT). The presented SQE model is a signal processing technique, which can be implemented in current microphones for predicting the sound quality. The proposed method extracts objective psychoacoustic metrics including loudness, sharpness, roughness, and tonality from sound samples, by using a special selection of multi-level nodes of the WPT combined with a trained ANN. The model is optimized using the particle swarm optimization (PSO) and the back propagation (BP) algorithms. The obtained results reveal that the proposed model shows the lowest mean square error and the highest correlation with human perception while it has the lowest computational cost compared to those of the other models and software.
    Źródło:
    Archives of Acoustics; 2019, 44, 3; 561-573
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Wavelet Packet Transform based Speech Enhancement via Two-Dimensional SPP Estimator with Generalized Gamma Priors
    Autorzy:
    Sun, P.
    Qin, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/177782.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    speech enhancement
    speech presence probability
    wavelet packet transform
    two-dimensional Teager energy operator
    Opis:
    Despite various speech enhancement techniques have been developed for different applications, existing methods are limited in noisy environments with high ambient noise levels. Speech presence probability (SPP) estimation is a speech enhancement technique to reduce speech distortions, especially in low signalto-noise ratios (SNRs) scenario. In this paper, we propose a new two-dimensional (2D) Teager-energyoperators (TEOs) improved SPP estimator for speech enhancement in time-frequency (T-F) domain. Wavelet packet transform (WPT) as a multiband decomposition technique is used to concentrate the energy distribution of speech components. A minimum mean-square error (MMSE) estimator is obtained based on the generalized gamma distribution speech model in WPT domain. In addition, the speech samples corrupted by environment and occupational noises (i.e., machine shop, factory and station) at different input SNRs are used to validate the proposed algorithm. Results suggest that the proposed method achieves a significant enhancement on perceptual quality, compared with four conventional speech enhancement algorithms (i.e., MMSE-84, MMSE-04, Wiener-96, and BTW).
    Źródło:
    Archives of Acoustics; 2016, 41, 3; 579-590
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Applications and Comparison of Continuous Wavelet Transforms on Analysis of A-wave Impulse Noise
    Autorzy:
    Qin, J.
    Sun, P.
    Powiązania:
    https://bibliotekanauki.pl/articles/177117.pdf
    Data publikacji:
    2015
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    continuous wavelet transform (CWT)
    impulse noise signal processing
    time-frequency domain
    temporal and spectral resolutions
    noise-induced hearing loss
    A-wave impulse noise
    Opis:
    Noise induced hearing loss (NIHL) is a serious occupational related health problem worldwide. The A-wave impulse noise could cause severe hearing loss, and characteristics of such kind of impulse noise in the joint time-frequency (T-F) domain are critical for evaluation of auditory hazard level. This study focuses on the analysis of A-wave impulse noise in the T-F domain using continual wavelet transforms. Three different wavelets, referring to Morlet, Mexican hat, and Meyer wavelets, were investigated and compared based on theoretical analysis and applications to experimental generated A-wave impulse noise signals. The underlying theory of continuous wavelet transform was given and the temporal and spectral resolutions were theoretically analyzed. The main results showed that the Mexican hat wavelet demonstrated significant advantages over the Morlet and Meyer wavelets for the characterization and analysis of the A-wave impulse noise. The results of this study provide useful information for applying wavelet transform on signal processing of the A-wave impulse noise.
    Źródło:
    Archives of Acoustics; 2015, 40, 4; 503-512
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-12 z 12

      Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies