MIT-World Peace University (MIT-WPU) is a top educational institute located in Pune, India. It is recognized within&nbsp;UGC under Government of Maharashtra Act No. XXXV 2017.&nbsp;

It is part of the MIT group of institutions (established in 1983) which covers 10+ campuses across India and has more than 50,000+ students enrolled across various disciplines at a given point of time. The institute houses 15 schools ranging from Engineering &amp; Technology, Design, Pharmacy, Commerce, Governance among others. It offers undergraduate, postgraduate and PhD programs among different disciplines.&nbsp;

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MIT World Peace University

World University root node

School of Electronics & Communication Engineering

Engineering and Technology

Lecture Notes in Networks and Systems

Vehicle Cluster Development

Multimedia Tools and Applications

Adaptive recurrent nonnegative matrix factorization with phase compensation for Single-Channel speech enhancement

Voice quality enhancement is a significant method for any speech communication model. Speech Enhancement (SE) and noise reduction approaches can significantly improve the perceptual voice quality of a hands-free communication system and increase the recognition rates of automatic speech recognition systems. Speech communications in real-world cases require high-performance enhancement techniques for addressing the distortions, which can corrupt the intelligibility and quality of the speech signal. Recent portable devices generally incorporate several microphones that can be easily used for improving signal quality. This paper plans to present a novel dual-channel SE model using the coherence function and heuristic concepts. The adaptive coherence function relates to the dual-microphone SE approach suitable for smartphones with primary and reference microphones. With this improved signal, the enhancement is performed by optimising denoising using Discrete Wavelet Transform (DWT) by Adaptive wind speed-based Deer Hunting Optimization Algorithm (AWS-DHOA). The considered objective function depends on the quality measure called Perceptual Evaluation of Speech Quality (PESQ) score. From the results, the RMSE of the proposed model using AWS-DHOA is 39.8%, 45.5%, 53.8% and 45.5% minimised than GWO-CFD, WOA-CFD, CSA-CFD, and RDA-CFD, respectively, on considering the babble noise. Finally, the comparative analysis confirmed that the proposed method improves speech quality and intelligibility by comparing diverse algorithms when different noise types corrupt the speech. © 2022 World Scientific Publishing Co.

Journal of Information and Knowledge Management

Automated Dual-Channel Speech Enhancement Using Adaptive Coherence Function with Optimised Discrete Wavelet Transform

The most essential work in a communication system is reconstructing a clean speech from a noisy environment which is a challenging problem in speech processing. The performance of speech processing system could increase by utilizing an effective speech enhancement technique in case of mobile phone, hearing aids, etc. An innovative speech enhancement technique may help in increasing the accuracy of speech recognition methods. In this paper a new approach has been introduced which deals with the implementation of dual channel speech enhancement technique utilizes the coherence function computed from the dual input signals without prior noise statistics for noise reduction. For post-processing, discrete wavelet transform (DWT) is used as a gain function which is set up by SNR values using coherence function. The proposed algorithm is applied in an environment where interfering speakers are present and gives a better result than other algorithms when the speech is corrupted by different noise types. © 2018 IEEE.

Second International Conference on Intelligent Computing and Control Systems(ICICCS)

Dual Channel Coherence Based Speech Enhancement with Wavelet Denoising

A Blind Source Separation with Fractional Calculus for Noise Reduction in Speech enhancement is proposed in this paper. Different strategies are available for reduction of noise. Fractional calculus has been recently applied in various zones like engineering, science, bio-engineering and finance. It has numerous applications, for example, use in differentiation, integral equations, signal processing, fluid mechanics, and electrochemistry. In this work speech processing signal application where Discrete Fractional Fourier Transform (DFRFT) is used which is an essential process for signal processing. DFRFT has DFT hermite Eigenvectors and retains the eigenvalue eigen operate relation as a fractional fourier transform that reconstruct the signal. For the purpose of noise reduction, Blind Source Separation has been utilizing which does not have prior knowledge of original signal. DFRFT algorithm and SNR are used to prove that the improvement of the processed enhanced signal as compared to the noisy signal. © 2017 IEEE.

2017 International conference on Microelectronic Devices, Circuits and Systems (ICMDCS)

A blind source separation with fractional calculus for noise reduction in speech enhancement

2017 International Conference on Computing, Communication, Control and Automation (ICCUBEA)

Implementation of Spectral Subtraction Using IBM in Simulink

Implementation of Auditory Filter Bank for Denoising Speech Signal using Simulink and MATLAB

Auditory-Based Transform (AT) is a function based on the impulse response of the basilar membrane in the cochlea. As the human auditory system utilizes the time and frequency localization of audio signals, AT can be the best suited algorithm for speech enhancement that is for reduction of noise in speech signal processing. The present paper deals with the implementation and comparison of Auditory Transform with two other algorithms:-Spectral subtraction and Wiener filter. Evaluation of intelligibility and comparison among the three algorithms has been done based on a recently proposed objective parameter, Normalized Covariance Measure, along with PSNR and Spectrogram. © 2015 IEEE.