  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.
