High spectral covariation between frequency channels contributes to clear speech intelligibility

Abstract

Speech signals are acoustically redundant, which could explain why sentence intelligibility is fairly robust even when sentences are acoustically degraded. We investigated the contributions to sentence intelligibility of clear speech redundancy encoded as patterns of spectrotemporal covariation between frequency channels. Participants (N = 16) transcribed 120 clear-speech English sentences acoustically degraded to 5, 8, or 15 frequency bands derived from an ERB-scaled filter bank. Before the acoustic degradation, each sentence was expressed as a linear combination of principal component eigenvectors representing different patterns of covariation between channels. Half of the sentences preserved the channels providing larger score magnitudes for the eigenvector accounting for more spectral covariance (high-covariance condition). These channels represented the spectral covariation patterns that were more dominant in each sentence. The other half of the sentences preserved the bands conveying larger score magnitudes for the eigenvector accounting forless spectral covariance (low-covariance condition). These bands represented the spectral covariation patterns that were less dominant. Participants yielded significantly better transcription accuracy in the high-covariance condition (mixed-effects, ps < 0.0021). Critically, accuracy in this condition was higher than 56% on average for as few as 5 bands. These findings indicate that clear speech intelligibility is supported by patterns of spectral covariation between frequency bands.