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Wyszukujesz frazę "Farooq, O." wg kryterium: Autor


Wyświetlanie 1-4 z 4
Tytuł:
A Multi-Level Robust and Perceptually Transparent Blind Audio Watermarking Scheme Using Wavelets
Autorzy:
Husain, F.
Farooq, O.
Khan, E.
Powiązania:
https://bibliotekanauki.pl/articles/176447.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
digital audio watermarking
robustness
single-level watermarking
multi-level watermarking
payload capacity
Opis:
In this paper, a robust and perceptually transparent single-level and multi-level blind audio watermark- ing scheme using wavelets is proposed. A randomly generated binary sequence is used as a watermark, and wavelet function coding is used to embed the watermark sequence in audio signals. Multi-level wa- termarking is used to enhance payload capacity and can be used for a different level of security. The robustness of the scheme is evaluated by applying different attacks such as filtering, sampling rate al- teration, compression, noise addition, amplitude scaling, and cropping. The simulation results obtained show that the proposed watermarking scheme is resilient to various attacks except cropping. Perceptual transparency of watermark is measured by using Perceptual Evaluation of Audio Quality (PEAQ) ba- sic model of ITU-R (PEAQ ITU-R BS.1387) on Speech Quality Assessing Material (SQAM) given by European Broadcasting Union (EBU). Average Objective Difference Grade (ODG) measured for this method is −0.067 and −0.080 for single-level and multi-level watermarked audio signals, respectively. In the proposed single-level digital audio watermarking scheme, the payload capacity is increased by 19.05% as compared to the single-level Chirp-Based Digital Audio Watermarking (CB-DAWM) scheme.
Źródło:
Archives of Acoustics; 2014, 39, 4; 529-539
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comparative Study of Visual Feature for Bimodal Hindi Speech Recognition
Autorzy:
Upadhyaya, P.
Farooq, O.
Abidi, M. R.
Varshney, P.
Powiązania:
https://bibliotekanauki.pl/articles/177705.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Aligarh Muslim University audio visual corpus
AVASR
bimodal
DCT
DWT
Opis:
In building speech recognition based applications, robustness to different noisy background condition is an important challenge. In this paper bimodal approach is proposed to improve the robustness of Hindi speech recognition system. Also an importance of different types of visual features is studied for audio visual automatic speech recognition (AVASR) system under diverse noisy audio conditions. Four sets of visual feature based on Two-Dimensional Discrete Cosine Transform feature (2D-DCT), Principal Component Analysis (PCA), Two-Dimensional Discrete Wavelet Transform followed by DCT (2D-DWT-DCT) and Two-Dimensional Discrete Wavelet Transform followed by PCA (2D-DWT-PCA) are reported. The audio features are extracted using Mel Frequency Cepstral coefficients (MFCC) followed by static and dynamic feature. Overall, 48 features, i.e. 39 audio features and 9 visual features are used for measuring the performance of the AVASR system. Also, the performance of the AVASR using noisy speech signal generated by using NOISEX database is evaluated for different Signal to Noise ratio (SNR: 30 dB to -10 dB) using Aligarh Muslim University Audio Visual (AMUAV) Hindi corpus. AMUAV corpus is Hindi continuous speech high quality audio visual databases of Hindi sentences spoken by different subjects.
Źródło:
Archives of Acoustics; 2015, 40, 4; 609-619
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Frequency Selection Based Separation of Speech Signals with Reduced Computational Time Using Sparse NMF
Autorzy:
Varshney, Y. V.
Abbasi, Z. A.
Abidi, M. R.
Farooq, O.
Powiązania:
https://bibliotekanauki.pl/articles/176829.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
sparse NMF
non-negative matrix factorisation
mixed speech recognition
machine learning
Opis:
Application of wavelet decomposition is described to speed up the mixed speech signal separation with the help of non-negative matrix factorisation (NMF). It is assumed that the basis vectors of training data of individual speakers had been recorded. In this paper, the spectrogram magnitude of a mixed signal has been factorised with the help of NMF with consideration of sparseness of speech signals. The high frequency components of signal contain very small amount of signal energy. By rejecting the high frequency components, the size of input signal is reduced, which reduces the computational time of matrix factorisation. The signal of lower energy has been separated by using wavelet decomposition. The present work is done for wideband microphone speech signal and standard audio signal from digital video equipment. This shows an improvement in the separation capability using the proposed model as compared with an existing one in terms of correlation between separated and original signals. Obtained signal to distortion ratio (SDR) and signal to interference ratio (SIR) are also larger as compare of the existing model. The proposed model also shows a reduction in computational time, which results in faster operation.
Źródło:
Archives of Acoustics; 2017, 42, 2; 287-295
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Effect of foliar application of zinc oxide on growth and photosynthetic traits of cherry tomato under calcareous soil conditions
Autorzy:
Sardar, H.
Naz, S.
Ejaz, S.
Farooq, O.
Rehman, A.
Javed, M.S.
Akhtar, G.
Powiązania:
https://bibliotekanauki.pl/articles/13078188.pdf
Data publikacji:
2021
Wydawca:
Uniwersytet Przyrodniczy w Lublinie. Wydawnictwo Uniwersytetu Przyrodniczego w Lublinie
Źródło:
Acta Scientiarum Polonorum. Hortorum Cultus; 2021, 20, 1; 91-99
1644-0692
Pojawia się w:
Acta Scientiarum Polonorum. Hortorum Cultus
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

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