Proceedings of the 42nd International Conference on Acoustics, Speech and Signal Processing (ICASSP2017), New Orleans, LA, March 5-9, 2017
A Multiple Bandwidth Objective Speech Intelligibility Estimator Based on Articulation Index Band Correlations and Attention
Cite This Publication
Stephen D. Voran, “A Multiple Bandwidth Objective Speech Intelligibility Estimator Based on Articulation Index Band Correlations and Attention,” in Proceedings of the 42nd International Conference on Acoustics, Speech and Signal Processing (ICASSP2017) New Orleans, LA, March 5-9, 2017.
Stephen D. Voran 
Abstract: 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.
Keywords: modified rhyme test (MRT); speech intelligibility; ABC-MRT; articulation index; objective estimator; ABC-MRT16
For technical information concerning this report, contact:
Stephen D. Voran
Institute for Telecommunication Sciences
(303) 497-3839
svoran@ntia.gov
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