Index of content:
Volume 113, Issue 4, April 2003
- ARCHITECTURAL ACOUSTICS 
113(2003); http://dx.doi.org/10.1121/1.1558375View Description Hide Description
The spatial correlation has previously been investigated for tonal and narrow-band sound fields. This letter presents an experimental investigation of the spatial correlation coefficients in a reverberation chamber driven by broadband signals. The main objective is to verify recent theoretical results for broadband spatial correlation in diffuse sound fields. Experimental results show good agreement with theoretical predictions when the frequency band of the sound field is entirely above the Schroeder frequency.
113(2003); http://dx.doi.org/10.1121/1.1558373View Description Hide Description
Speech transmission index (STI) is an important objective parameter concerning speech intelligibility for sound transmission channels. It is normally measured with specific test signals to ensure high accuracy and good repeatability. Measurement with running speech was previously proposed, but accuracy is compromised and hence applications limited. A new approach that uses artificial neural networks to accurately extract the STI from received running speech is developed in this paper. Neural networks are trained on a large set of transmitted speech examples with prior knowledge of the transmission channels’ STIs. The networks perform complicated nonlinear function mappings and spectral feature memorization to enable accurate objective parameter extraction from transmitted speech. Validations via simulations demonstrate the feasibility of this new method on a one-net-one-speech extract basis. In this case, accuracy is comparable with normal measurement methods. This provides an alternative to standard measurement techniques, and it is intended that the neural network method can facilitate occupied room acoustic measurements.