Performance Analysis of Adaptive Noise Canceller Employing NLMS Algorithm

Afroz, F; Huq, Asadul; Sandrasegaran, Kumbesan

doi:10.5121/ijwmn.2015.7204

Cited by 15 publications

(13 citation statements)

References 17 publications

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“…Though the computation speed of LPC is good and provides with accurate parameters of speech, but it generates residual error as output. This means that some amount of important speech gets left in the residue resulting in poor speech quality [9,10]. The Linear Predictive Cepstral Coefficient (LPCC) is an extension of the LPC technique, where a cepstral analysis is executed after completing the LPC analysis in order to obtain the corresponding cepstral coefficients [11].…”

Section: Feature Extractionmentioning

confidence: 99%

“…Among those techniques, the most widely used feature extraction methods is Mel frequency Cepstral Coefficient (MFCC) in the field of ASR [8,14]. MFCC provides good discrimination [5] and low correlation between coefficients, but MFCC performance might be affected by the number of filters [10] and does not give accurate results if there are background noise [8].…”

Section: Feature Extractionmentioning

confidence: 99%

“…This paper focuses on DTW, which is used to find an optimal alignment between two given (time-dependent) sequences under certain restrictions intuitively. DTW feature classifier is useful for isolated word recognition in a limited dictionary, though it has O(n2v), high complexity for larger dictionary [10,12,15]. Hidden Markov Models (HMM) has been widely used in lot of speech recognition applications because of its high reliability [12].…”

Section: Pattern Matchingmentioning

confidence: 99%

See 2 more Smart Citations

A Normalized Least Mean Square and Dynamic Time Warping (DTW) Algorithm for an Intelligent Quran Tutoring System

Mazumder¹,

Salam²

2018

IJET

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Al-Quran is the most recited holy book in the Arabic language. Over 1.3-billion Muslim all over the world have an obligation to recite and learn Al-Quran. Learners from non-Arabic as well as from Arabic speaking communities face difficulties with Al-Quran recitation in the absence of a teacher (ustad) around. Advancement in speech recognition technology creates possible solutions to develop a system that has a capability to auricularly discern and validate the recitation. This paper investigates the speech recognition accuracy of template-based acoustic models and propose enhancement methods to improve the accuracy. A new scheme consists of enhancement of Normalized Least Mean Square (NLMS) and Dynamic Time Warping (DTW) algorithms have been proposed. The performance of the speech recognition accuracy was further improved by incorporating an adaptive optimal filtering with modified humming window for MFCC (Mel-frequency cepstral coefficients) using matching technique dynamic programming (DP), DTW (Dynamic Time Wrapping). The proposed scheme increases 5.5% of relative improvement in recognition accuracy achieved over conventional speech recognition process.

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Section: Feature Extractionmentioning

confidence: 99%

Section: Feature Extractionmentioning

confidence: 99%

Section: Pattern Matchingmentioning

confidence: 99%

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A Normalized Least Mean Square and Dynamic Time Warping (DTW) Algorithm for an Intelligent Quran Tutoring System

Mazumder¹,

Salam²

2018

IJET

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“…The work of Afroz et al [24] and Gupta et al [25] have conducted a comparative analysis of different adaptive filter for evaluating its performance for speech enhancement in terms of PSNR, SNR, and MSE. Gbadamosi et al [26] designed signal-denoising framework based on Fourier transform and non-parametric modeling for noise elimination in GSM speech signal.…”

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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“…The use of adaptive digital filter in noise cancelling system is at the core for achieving this adaptation capability of the system. In adaptive filter, the filter coefficients can be modified intelligently using adaptive algorithms so that the filter can keep track to the instantaneous changes being occurred in its input characteristics [3]. A range of adaptive algorithms has been proposed to achieve optimum system performance in many applications.…”

mentioning

confidence: 99%

Cancellation of White and Color Noise with Adaptive Filter Using LMS Algorithm

Ahmed¹,

Afroz²,

Tawsif³

et al. 2015

IJWMN

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In this paper, the performances of adaptive noise cancelling system employing Least Mean Square (LMS) algorithm are studied considering both white Gaussian noise (Case 1) and colored noise (Case 2) situations. Performance is analysed with varying number of iterations, Signal to Noise Ratio (SNR) and tap size with considering Mean Square Error (MSE) as the performance measurement criteria. Results show that the noise reduction is better as well as convergence speed is faster for Case 2 as compared with Case 1. It is also observed that MSE decreases with increasing SNR with relatively faster decrease of MSE in Case 2 as compared with Case 1, and on average MSE increases linearly with increasing number of filter coefficients for both type of noise situations. All the experiments have been done using computer simulations implemented on MATLAB platform.

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Performance Analysis of Adaptive Noise Canceller Employing NLMS Algorithm

Abstract: ABSTRACT

Cited by 15 publications

References 17 publications

A Normalized Least Mean Square and Dynamic Time Warping (DTW) Algorithm for an Intelligent Quran Tutoring System

A Normalized Least Mean Square and Dynamic Time Warping (DTW) Algorithm for an Intelligent Quran Tutoring System

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

Cancellation of White and Color Noise with Adaptive Filter Using LMS Algorithm

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