Technical Report: A New Decision-Theory-Based Framework for Echo Canceler Control

TL;DR

This paper introduces a decision-theory-based framework for echo canceler control that improves detection of double-talk and channel changes, enabling more reliable adaptive filter operation in echo cancellation systems.

Contribution

It extends traditional detection strategies to a classification approach using decision theory, allowing continuous control and analytical performance assessment.

Findings

The proposed method accurately classifies echo canceler states.

Analytical error probability bounds are derived for the classification.

Simulations demonstrate improved reliability over existing detectors.

Abstract

A control logic has a central role in many echo cancellation systems for optimizing the performance of adaptive filters while estimating the echo path. For reliable control, accurate double-talk (DT) and channel change (CC) detectors are usually incorporated to the echo canceler. This work expands the usual detection strategy to define a classification problem characterizing four possible states of the echo canceler operation. The new formulation allow the use of decision theory to continuously control the transitions among the different modes of operation. The classification rule reduces to a low cost statistics for which it is possible to determine the probability of error under all hypotheses, allowing the classification performance to be accessed analytically. Monte Carlo simulations using synthetic and real data illustrate the reliability of the proposed method.