A multiple bandwidth objective speech intelligibility estimator based on articulation index band correlations and attention

摘要

We present ABC-MRT16-a new algorithm for objective estimation of speech intelligibility following the Modified Rhyme Test (MRT) paradigm. ABC-MRT16 is simple, effective and robust. When compared to subjective MRT data from 367 diverse conditions that include coding, noise, frame erasures, and much more, ABC-MRT16 (containing just one optimized parameter) yields a very high Pearson correlation (above 0.95) and a remarkably low RMS estimation error (below 7% of full scale.) We attribute these successes to concise modeling of core human processes in audition and forced-choice word selection. On each trial, ABC-MRT16 gathers word selection evidence in the form of articulation index band correlations and then uses a simple attention model to perform word selection using the best available evidence. Attending to best evidence allows ABC-MRT16 to work well for narrowband, wideband, superwideband, and fullband speech and noise without any bandwidth detection algorithm or side information.