z-logo
open-access-imgOpen Access
Evaluating signal-to-noise ratios, loudness, and related measures as indicators of airborne sound insulation
Author(s) -
H. K. Park,
John S. Bradley
Publication year - 2009
Publication title -
the journal of the acoustical society of america
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.619
H-Index - 187
eISSN - 1520-8524
pISSN - 0001-4966
DOI - 10.1121/1.3192347
Subject(s) - loudness , acoustics , annoyance , intelligibility (philosophy) , soundproofing , speech recognition , background noise , sound exposure , noise (video) , computer science , mathematics , sound (geography) , physics , artificial intelligence , philosophy , epistemology , image (mathematics)
Subjective ratings of the audibility, annoyance, and loudness of music and speech sounds transmitted through 20 different simulated walls were used to identify better single number ratings of airborne sound insulation. The first part of this research considered standard measures such as the sound transmission class the weighted sound reduction index (R(w)) and variations of these measures [H. K. Park and J. S. Bradley, J. Acoust. Soc. Am. 126, 208-219 (2009)]. This paper considers a number of other measures including signal-to-noise ratios related to the intelligibility of speech and measures related to the loudness of sounds. An exploration of the importance of the included frequencies showed that the optimum ranges of included frequencies were different for speech and music sounds. Measures related to speech intelligibility were useful indicators of responses to speech sounds but were not as successful for music sounds. A-weighted level differences, signal-to-noise ratios and an A-weighted sound transmission loss measure were good predictors of responses when the included frequencies were optimized for each type of sound. The addition of new spectrum adaptation terms to R(w) values were found to be the most practical approach for achieving more accurate predictions of subjective ratings of transmitted speech and music sounds.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom