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Room acoustic parameter extraction from music signals

Kendrick, P; Cox, TJ; Zhang, Y; Chambers, JA; Li, FF

Authors

P Kendrick

Y Zhang

JA Chambers

FF Li



Abstract

A new method, employing machine learning techniques and a modified low frequency envelope spectrum estimator, for estimating important room acoustic parameters including reverberation time (RT) and early decay time (EDT) from received music signals has been developed. It overcomes drawbacks found in applying music signals directly to the envelope spectrum detector developed for the estimation of RT from speech signals. The octave band music signal is first separated into sub bands corresponding to notes on the equal temperament scale and the level of each note normalised before applying an envelope spectrum detector. A typical artificial neural network is then trained to map these envelope spectra onto RT or EDT. Significant improvements in estimation accuracy were found and further investigations confirmed that the non-stationary nature of music envelopes is a major technical challenge hindering accurate parameter extraction from music and the proposed method to some extent circumvents the difficulty.

Citation

Kendrick, P., Cox, T., Zhang, Y., Chambers, J., & Li, F. (2006). Room acoustic parameter extraction from music signals. Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing, 5, V-801. https://doi.org/10.1109/ICASSP.2006.1661397

Journal Article Type Article
Conference Name 2006 IEEE International Conference on Acoustics Speech and Signal Processing Proceedings
Publication Date Jan 1, 2006
Deposit Date May 11, 2016
Journal Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on (Volume:2 )
Print ISSN 1520-6149
Publisher Institute of Electrical and Electronics Engineers
Volume 5
Pages V-801
Book Title 2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings
DOI https://doi.org/10.1109/ICASSP.2006.1661397
Publisher URL http://dx.doi.org/10.1109/ICASSP.2006.1661397
Related Public URLs http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=11024
Additional Information Event Type : Conference