A Perceptual Approach to Reduce Musical Noise Phenomenon with Wiener Denoising Technique

Assessment of musical noise using localization of isolated peaks in time-frequency domain

“…Based in this hypothesis, which is consistent with the observations given in previous works [1,10,8,3,15], we develop in the next section a methodology to extract from a spectrogram the regions that correspond to the shape of the expected "spots", in order to quantify them.…”

“…In the literature, a wide collection of methods have been proposed to reduce musical noise, by improving the estimation of timefrequency masks [4,5,6,7,8], post-processing techniques [2,9,10,11], or in the context of sparse representations [12,13]. The evaluation of the effectiveness is in most cases exclusively based on listening tests assessing the overall quality of denoised signals.…”

Speech Enhancement Based on Student <formula formulatype="inline"><tex Notation="TeX">$t$</tex></formula> Modeling of Teager Energy Operated Perceptual Wavelet Packet Coefficients and a Custom Thresholding Function

“…We can divide these methods in mainly three categories based on their domains of operation, namely time domain, frequency domain and time-frequency domain. Time domain methods include the subspace approach [4], [5], frequency domain methods include methods based on discrete cosine transform [6], spectral subtraction [7], [8], minimum mean square error (MMSE) estimator [2], [4], wiener filtering [9], [10] and time frequency-domain methods involve the employment of the family of wavelets [11]- [15]. Time domain subspace method provides a tradeoff between speech distortion and residual noise.…”

New Speech Enhancement based on Discrete Orthonormal Stockwell Transform

“…Also, the Wiener estimator has a moderate computation load, but it offers no mechanism to control tradeoff between speech distortion and residual noise. Thus, the one major problem of wiener filter based methods [2]- [3] is the requirement of obtaining clean speech statistics necessary for their implementation. Among the methods using time-frequency analyses, an approach of reducing different types of noise that corrupt the clean speech is the use of Discrete Wavelet Transform (DWT) [5]- [9], which is a superior alternative to the analyses based on Short Time Fourier Transform (STFT).…”

“…The literature is enriched by many works which treat several methods for speech enhancement has been developed and investigated such as Discrete Fourier transformer (DFT), Discrete Cosine Transformer (DCT), Karhunen-Loeve transformer (KLT),Wiener filtering [2,3],Spectral Subtraction [1], Wavelet Transform (WT) [5][6][7][8][22][23][24][25][26], etc. All the methods have their advantages and inconveniences.…”