Acoustic Echo and Noise Cancellation System for Hand-Free Telecommunication using Variable Step Size Algorithms

In this paper, acoustic echo cancellation with doubletalk detection system is implemented for a hand-free telecommunication system using Matlab. Here adaptive noise canceller with blind source separation (ANC-BSS) system is proposed to remove both background noise and far-end speaker echo signal in presence of double-talk. During the absence of double-talk, far-end speaker echo signal is cancelled by adaptive echo canceller. Both adaptive noise canceller and adaptive echo canceller are implemented using LMS, NLMS, VSLMS and VSNLMS algorithms. The normalized cross-correlation method is used for double-talk detection. VSNLMS has shown its superiority over all other algorithms both for double-talk and in absence of double-talk. During the absence of double-talk it shows its superiority in terms of increment in ERLE and decrement in misalignment. In presence of double-talk, it shows improvement in SNR of near-end speaker signal

Acoustic echo and noise canceller for personal hands-free video IP phone

This paper presents implementation and evaluation of a proposed acoustic echo and noise canceller (AENC) for videotelephony-enabled personal hands-free Internet protocol (IP) phones. This canceller has the following features: noise-robust performance, low processing delay, and low computational complexity. The AENC employs an adaptive digital filter (ADF) and noise reduction (NR) methods that can effectively eliminate undesired acoustic echo and background noise included in a microphone signal even in a noisy environment. The ADF method uses the step-size control approach according to the level of disturbance such as background noise; it can minimize the effect of disturbance in a noisy environment. The NR method estimates the noise level under an assumption that the noise amplitude spectrum is constant in a short period, which cannot be applied to the amplitude spectrum of speech. In addition, this paper presents the method for decreasing the computational complexity of the ADF process without increasing the processing delay to make the processing suitable for real-time implementation. The experimental results demonstrate that the proposed AENC suppresses echo and noise sufficiently in a noisy environment; thus, resulting in natural-sounding speech

Model-Based Method for Acoustic Echo Cancelation and Near-End Speaker Extraction: Non-negative Matrix Factorization, Journal of Telecommunications and Information Technology, 2018, nr 2

Rapid escalation of wireless communication and hands-free telephony creates a problem with acoustic echo in full-duplex communication applications. In this paper a simulation of model-based acoustic echo cancelation and near-end speaker extraction using statistical methods relying on nonnegative matrix factorization (NMF) is proposed. Acoustic echo cancelation using the NMF algorithm is developed and its implementation is presented, along with all positive, real time elements and factorization techniques. Experimental results are compared against the widely used existing adaptive algorithms which have a disadvantage in terms of long impulse response, increased computational load and wrong convergence due to change in near-end enclosure. All these shortcomings have been eliminated in the statistical method of NMF that reduces echo and enhances audio signal processing

Journal of Telecommunications and Information Technology, 2018, nr 2

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