Frequency-importance functions for words in high- and low-context sentences.

The relative importance and absolute contributions of various spectral regions to speech intelligibility under conditions of either neutral or predictable sentential context were examined. Specifically, the frequency-importance functions for a set of monosyllabic words embedded in a highly predictive sentence context versus a sentence with little predictive information were developed using Articulation Index (AI) methods. Forty-two young normal-hearing adults heard sentences presented at signal-to-noise ratios from -8 to +14 dB in a noise shaped to conform to the peak spectrum of the speech. Results indicated only slight differences in 1/3-octave importance functions due to differences in semantic context, although the crossovers differed by a constant 180 Hz. Methodological and theoretical aspects of parameter estimation in the AI model are discussed. The results suggest that semantic context, as defined by these conditions, may alter frequency-importance relationships in addition to the dynamic range over which intelligibility rises.

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