ASA - ANSI/ASA S3.5
American National Standard Methods for Calculation of the Speech Intelligibility Index
|Publication Date:||6 June 1997|
The predictions of this Standard apply to listening conditions where the input variables of the Speech Intelligibility Index (Sll) model can be accurately estimated. The input variables include the equiva- lent speech spectrum level, the equivalent noise spectrum level, and the equivalent hearing thresh- old level. This includes the conditions where either speech or noise may not exist as directly measur- able physical quantities (e.g., conditions where speech correlated noise is present, such as rever- berated speech) but where equivalent speech spectrum level, equivalent noise spectrum level, and equivalent hearing threshold level can. never- theless. be calculated. The predictions made by use of this Standard are correct only on the aver- age. that is, across a group of talkers and a group of listeners of both genders. The scope of the Standard is limited to natural speech, otologically normal listeners, and communication conditions which do not include multiple, sharply filtered bands of speech or sharply filtered noise. In addi- tion, the listeners should have no linguistic or cog- nitive deficiencies with respect to the language used.
This Standard defines methods for computing a measure, called the Speech Intelligibility Index (Sll). that is highly correlated with the intelligibility of speech under a variety of adverse listening con- ditions, such as noise masking, filtering, and rever- beration. The Sll is computed from acoustical measurements or estimates of speech spectrum level, from noise spectrum level, and from psy- choacoustical measurements or estimates of hear- ing threshold level. Various frequencies contribute different amounts to speech intelligibility, and. within a certain range, a higher speech-to-noise ratio contributes to intelligibility. By measuring the speech-to-noise ratio in each contributing fre- quency band and adding the results, the intelligi- bility of a speech communication system can be predicted.