Abstract
The Articulation Index (AI), later revised and standardized as the Speech Intelligibility Index (SII), and the Speech Transmission Index (STI) have been successful in predicting speech intelligibility from acoustic measurements. Both approaches calculate the index as sum of additive audibility contributions from different frequency bands. Allen (2003) noted that a similar additivity property also holds for Shannon’s information-theoretic concept of Channel Capacity. Allen showed that the contributions to channel capacity are (approximately) linearly related to the signal-to-noise ratio (in dB), just like the audibility contributions to the AI, and suggested that the AI is actually a kind of channel-capacity measure. This would be a fundamental information-theoretical basis for the empirical success of AI theory.
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