Proceedings of the ACE Challenge Workshop - a satellite event of IEEE-WASPAA (2015)

TL;DR

This paper discusses the ACE Challenge Workshop which focused on evaluating algorithms for blind estimation of room acoustics parameters like T60 and DRR directly from speech signals, promoting research in this area.

Contribution

It introduces a benchmarking effort to assess state-of-the-art algorithms for blind acoustic parameter estimation from speech signals.

Findings

Algorithms were evaluated against ground truth data.

The challenge promoted advancements in blind acoustic parameter estimation.

Results highlighted current capabilities and gaps in the field.

Abstract

Several established parameters and metrics have been used to characterize the acoustics of a room. The most important are the Direct-To-Reverberant Ratio (DRR), the Reverberation Time (T60) and the reflection coefficient. The acoustic characteristics of a room based on such parameters can be used to predict the quality and intelligibility of speech signals in that room. Recently, several important methods in speech enhancement and speech recognition have been developed that show an increase in performance compared to the predecessors but do require knowledge of one or more fundamental acoustical parameters such as the T60. Traditionally, these parameters have been estimated using carefully measured Acoustic Impulse Responses (AIRs). However, in most applications it is not practical or even possible to measure the acoustic impulse response. Consequently, there is increasing research activity in the estimation of such parameters directly from speech and audio signals. The aim of this challenge was to evaluate state-of-the-art algorithms for blind acoustic parameter estimation from speech and to promote the emerging area of research in this field. Participants evaluated their algorithms for T60 and DRR estimation against the 'ground truth' values provided with the data-sets and presented the results in a paper describing the method used.