Single Channel Speech Enhancement: Using Wiener Filtering with Recursive Noise Estimation

Upadhyay, Navneet; Jaiswal, Rahul

doi:10.1016/j.procs.2016.04.061

Cited by 40 publications

(13 citation statements)

References 5 publications

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“…It depends on the filter transfer function from sample to sample based on the speech signal statistics; the local mean and the local variance and it is implemented in frequency domain. The proposed algorithm is similar to the work done in [12], but the major difference exists in the domain of computations, the above existed work done in spectral domain and the proposed work completely done in time domain.…”

Section: Introductionmentioning

confidence: 98%

“…It outperforms the conventional VAD by using two separate thresholds for the likelihood ratio test (LRT), which are resulted from temporal correlations between current and previous frames. Upadhyay et al [12] proposes the recursive noise estimation algorithm, in this the noise power is updated based on present and previous values of it with the help of a smoothing parameter. It depends on the filter transfer function from sample to sample based on the speech signal statistics; the local mean and the local variance and it is implemented in frequency domain.…”

Section: Introductionmentioning

confidence: 99%

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Short-term uncleaned signal to noise threshold ratio based end-to-end time domain speech enhancement in digital hearing aids

Nimmagadda¹,

Swamy

Prathima³

et al. 2022

IJEECS

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This paper presents the improvements in the combined solution for the noise estimation and the speech enhancement in digital hearing aids in time domain. This study focuses on the single channel statistical temporal speech enhancement using adaptive Wiener filtering. In this technique, the noise is updated based on the short-term uncleaned signal to noise threshold ratio (ST-USNTR) of the frame. It works best if and only if the back ground noise level is low compared to that of speech of interest. We considered the time domain algorithms in order to consider the time varying nature of speech signal. The performance of the proposed algorithm is evaluated for speech signal with seven ty pes of noises and three signal to noise ratios (SNR) levels in each type of noise. From the results, it is clear that the basic level of adaptive speech enhancement is obtained using statistical parameters of noisy speech without the need for reference input.

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Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Short-term uncleaned signal to noise threshold ratio based end-to-end time domain speech enhancement in digital hearing aids

Nimmagadda¹,

Swamy

Prathima³

et al. 2022

IJEECS

View full text Add to dashboard Cite

show abstract

“…The functional expansion using trigonometric expansion, 31,32 Legendre Expansion, 33 Cubic Spline Expansion, [34][35][36] Volterra expansion, 37 Hammerstein expansion, 38 Weiner filter 39 are discussed in literature. Some of these algorithms have been employed for active noise control in communication systems but very few have been designed for shunt compensation.…”

Section: Introductionmentioning

confidence: 99%

Development and performance analysis of cubic Bezier functional expansion‐based adaptive filter for grid‐interfaced PV system

Arora

Singh

2021

Int Trans Electr Energ Syst

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A non-linear cubic Bezier-functional expansion-based adaptive filter (CB-FEBAF) has been designed for achieving shunt compensation in this article. The algorithm is developed for mitigating current-based power quality problems such as harmonics in supply current, reactive VAR compensation, active power compensation, power factor improvement, load balancing, and so on. The CB-FEBAF is developed using Bezier curve expansion of the input signal. The functional expansion-based real time and online training converges fast and shows fast response over offline techniques such as neural network and neuro-fuzzy-based algorithms. The designed CB-FEBAF controller is trained online using gradient descent least mean square algorithm to extract the fundamental component of the load current. Moreover, the feedforward active power term corresponding to PV power contribution has been added to the developed controller. This helps to overcome the challenges in the integration of renewable energy-based distribution systems. The proposed controller is compared with non-adaptive synchronous reference frame theory, backpropagation neural network, and legendre-based functional neural network. Hardware results prove the multifunctional capabilities of the developed approach.

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“…Through performance analysis presented mechanism found to be effective in terms of PSNR and MSE. Upadhyay and Jaiswal [21] use an iterative noise assessment procedure with Wiener filtering approach for enhancing single channel speech. Premananda and Uma [22] have introduced a psychoacousticbased gain regulator for background noise removal and speech signal improvement in mobile telephony communication.…”

Section: Introductionmentioning

confidence: 99%

A novel and integrated architecture for identification and cancellation of noise from GSM signal

Rekha¹,

Jabeen

2019

IJECE

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There are multiple reasons for the evolution as well as the presence of noise over transmitted GSM signal. In spite of various approaches towards noise cancellation techniques, there are less applicable techniques for controlling noise in acoustic GSM signal. Therefore, the proposed manuscript presents an integrated modelling which performs modelling of noise identification that could significantly assist in successful noise cancellation. The proposed system uses three different approach viz. i) stochastic based approach for noise modelling, ii) analytical-based approach where allocated power acts as one of the prominent factors of noise, and iii) wavelet-based approach for effective decomposition of GSM signal for assisting better noise cancellation technique followed by better retention of signal quality. Simulated in MATLAB, the study outcome shows that it offers a cost-effective implementation, A Practical Approach for Noise identification, and Effective Noise Cancellation with Signal quality retention. The proposed system offers approximately 24% of enhancement in noise reduction as compared to any existing digital filters with 1.6 seconds faster in processing speed.

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Single Channel Speech Enhancement: Using Wiener Filtering with Recursive Noise Estimation

Cited by 40 publications

References 5 publications

Short-term uncleaned signal to noise threshold ratio based end-to-end time domain speech enhancement in digital hearing aids

Short-term uncleaned signal to noise threshold ratio based end-to-end time domain speech enhancement in digital hearing aids

Development and performance analysis of cubic Bezier functional expansion‐based adaptive filter for grid‐interfaced PV system

A novel and integrated architecture for identification and cancellation of noise from GSM signal

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