Revisiting Algorithms for Predicting the Articulation Loss of Consonants Alcons
Algorithms that have been proposed for predicting speech intelligibility based on the articulation loss of consonants Alcons are revisited. The simplest algorithm, known as the architectural form of the Peutz equation, is discussed and rederived using a technique to find forms of imperical equations. It is shown that other Peutz algorithms, which use measured values of room acoustical quantities for estimating Alcons, are based on Fletcher's articulation index concept, which is a quantitative measure of a communications system for transmitting the speech sounds. When compared for diffuse sound fields with ideal exponential decays, these algorithms provide similar predictions because they were all developed from the same experimental data. Unlike the speech transmission index STI and the useful-to-detrimental sound ratio U50, speech intelligibility predictions based on the Alcons algorithms do not take into account the effects of earlier reflections, single echoes, and the frequency dependence of relevant parameters. These limitations of the Alcons algorithms are crucial for accurate predictions of speech intelligibility in rooms. It is shown that in smaller rooms with a diffuse sound field and ideal exponential decays, are highly correlated with each other, whereas Alcons is not uniquely correlated with either of these speech metrics. Speech intelligibility predictions based on STI and U50 are compared with Alcons predictions for the Harvard phonetically balanced (PB) word test. For this test it is shown that the STI and U50 speech intelligibility predictions are in good agreement, and that these metrics have equal sensitivity to speech being degraded by reverberation and ambient noise, whereas the Alcons algorithms underpredicted speech intelligibility as the signal-to-noise ratio decreased.
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