An improved algorithm for the estimation of the reverberation time (RT) from reverberant speech signals is presented. This blind estimation of the RT is based on a simple statistical model for the sound decay such that the RT can be estimated by means of a maximum-likelihood (ML) estimator. The proposed algorithm has a significantly lower computational complexity than previous ML-based algorithms for RT estimation. This is achieved by a downsampling operation and a simple pre-selection of possible sound decays. The new algorithm is more suitable to track time-varying RTs than related approaches. In addition, it can also estimate the RT in the presence of (moderate) background noise. The proposed algorithm can be employed to measure the RT of rooms from sound recordings without using a dedicated measurement setup. Another possible application is its use within speech dereverberation systems for hands-free devices or digital hearing aids.
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