Information redundancy across spectral regions for sentence recognition in noise

Abstract

Two approaches are examined to quantify the synergetic and redundant interactions across spectral regions for sentence recognition in noise. In one approach, the Speech Intelligibility Index is extended such that speech intelligibility is not only influenced by the speech audibility metrics in individual frequency bands but also their pairwise products to capture the synergetic and redundant interactions between pairs of bands. In a second approach, it is assumed that successful keyword recognition is determined by how many independent channels of information is received by the listener. Each channel of information may be uniquely carried by a frequency band, representing the independent contribution of that band, or shared among multiple bands, representing information redundancy. A previously collected dataset was re-analyzed using the two quantification approaches. For each of the 30 listeners in the dataset, correctness in keyword recognition in the IEEE sentences was available for 600 trials. From trial to trial, the sentence-in-noise stimuli varied in terms of signal-to-noise ratio and which frequency bands were removed from the spectrum via filtering. Both approaches provided consistent depictions of how information is shared across spectral regions for the IEEE sentences. Moreover, the information redundancies across frequency regions did not equally impact all listeners.