Extracting Room Reverberation Time from Speech Using Artificial Neural Networks
Cox, TJ, Li, FF and Darlington, P 2001, 'Extracting Room Reverberation Time from Speech Using Artificial Neural Networks' , Journal of the Audio Engineering Society, 49 (4) , pp. 219-230.Full text not available from this repository.
A novel method to extract the reverberation time from reverberated speech utterances is presented. In this study, speech utterances are restricted to pronounced digits; uncontrolled discourse is not considered. The reverberation times considered are wide band, within the frequency range of speech utterances. A multilayer feed forward neural network is trained on speech examples with known reverberation times generated by a room simulator. The speech signals are preprocessed by calculating short-term rms values. A second decision-based neural network is added to improve the reliability of the predictions. In the retrieve phase, the trained neural networks extract room reverberation times from speech signals picked up in the rooms to an accuracy of 0.1 s. This provides an alternative to traditional measurement methods and facilitates the occupied measurement of room reverberation times.
|Themes:||Subjects / Themes > Q Science > QC Physics > QC221-246 Acoustics - Sound
Subjects outside of the University Themes
|Schools:||Schools > School of the Built Environment
Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre (SIRC)
|Journal or Publication Title:||Journal of the Audio Engineering Society|
|Publisher:||Audio Engineering Society Inc|
|Depositing User:||H Kenna|
|Date Deposited:||11 Sep 2007 13:27|
|Last Modified:||05 Apr 2016 17:30|
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