ICASSP 2017accepted0 citations

Measuring, modelling and predicting perceived reverberation

Hamza A. Javed, Benjamin Cauchi, Simon Doclo, Patrick A. Naylor, Stefan Goetze

Abstract

This paper investigates the relationship between the perceived level of reverberation and parameters measured from the room impulse response (RIR), as well as the design of an instrumental measure that predicts this perceived level. We first present the results of an experimental listening test conducted to assess the level of perceived reverberation in speech captured by a single microphone, before analysing the gathered data to assess the influence of parameters such as the reverberation time (T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">60</sub> ) or the direct-to-reverberant ratio (DRR). Secondly, we use the results of this analysis to improve the signal based reverberation decay tail (R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DT</sub> ) measure, previously proposed by the authors to predict the perceived level of reverberation. The accuracy of the proposed measure is evaluated in terms of correlation with the subjective scores and compared to the performance of predictors using parameters extracted from the RIR. Results show that the proposed modifications to the RDT does improve its accuracy. Though still slightly outperformed by measures based on parameters of the RIR, we believe the proposed measure to be useful in scenarios in which the RIR or its parameters are unknown.

BibTeX
@inproceedings{icassp2017_measuringmodelli,
  title = {Measuring, modelling and predicting perceived reverberation},
  author = {Hamza A. Javed and Benjamin Cauchi and Simon Doclo and Patrick A. Naylor and Stefan Goetze},
  booktitle = {ICASSP 2017},
  year = {2017}
}
Measuring, modelling and predicting perceived reverberation · ICASSP 2017