Graduation Year

2003

Document Type

Thesis

Degree

M.S.E.E.

Degree Granting Department

Electrical Engineering

Major Professor

Wilfrido A. Moreno, Ph.D.

Committee Member

James T. Leffew, Ph.D.

Committee Member

Wei Qian, Ph.D.

Keywords

aec, nlms, dtd, nlp, matlab

Abstract

The rapid growth of technology in recent decades has changed the whole dimension of communications. Today people are more interested in hands-free communication. In such a situation, the use a regular loudspeaker and a high-gain microphone, in place of a telephone receiver, might seem more appropriate. This would allow more than one person to participate in a conversation at the same time such as a teleconference environment. Another advantage is that it would allow the person to have both hands free and to move freely in the room. However, the presence of a large acoustic coupling between the loudspeaker and microphone would produce a loud echo that would make conversation difficult. Furthermore, the acoustic system could become instable, which would produce a loud howling noise to occur.

The solution to these problems is the elimination of the echo with an echo suppression or echo cancellation algorithm. The echo suppressor offers a simple but effective method to counter the echo problem. However, the echo suppressor possesses a main disadvantage since it supports only half-duplex communication. Half-duplex communication permits only one speaker to talk at a time. This drawback led to the invention of echo cancellers. An important aspect of echo cancellers is that full-duplex communication can be maintained, which allows both speakers to talk at the same time.

This objective of this research was to produce an improved echo cancellation algorithm, which is capable of providing convincing results. The three basic components of an echo canceller are an adaptive filter, a doubletalk detector and a nonlinear processor. The adaptive filter creates a replica of the echo and subtracts it from the combination of the actual echo and the near-end signal. The doubletalk detector senses the doubletalk. Doubletalk occurs when both ends are talking, which stops the adaptive filter in order to avoid divergence. Finally, the nonlinear processor removes the residual echo from the error signal. Usually, a certain amount of speech is clipped in the final stage of nonlinear processing. In order to avoid clipping, a noise gate was used as a nonlinear processor in this research. The noise gate allowed a threshold value to be set and all signals below the threshold were removed. This action ensured that only residual echoes were removed in the final stage. To date, the real time implementation of echo an cancellation algorithm was performed by utilizing both a VLSI processor and a DSP processor. Since there has been a revolution in the field of personal computers, in recent years, this research attempted to implement the acoustic echo canceller algorithm on a natively running PC with the help of the MATLAB software.

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