Speech intelligibility prediction based on modulation frequency-selective processing.

Speech intelligibility models can provide insights regarding the auditory processes involved in human speech perception and communication. One successful approach to modelling speech intelligibility has been based on the analysis of the amplitude modulations present in speech as well as competing interferers. This review covers speech intelligibility models that include a modulation-frequency selective processing stage i.e., a modulation filterbank, as part of their front end. The speech-based envelope power spectrum model [sEPSM, Jørgensen and Dau (2011). J. Acoust. Soc. Am. 130(3), 1475-1487], several variants of the sEPSM including modifications with respect to temporal resolution, spectro-temporal processing and binaural processing, as well as the speech-based computational auditory signal processing and perception model [sCASP; Relaño-Iborra et al. (2019). J. Acoust. Soc. Am. 146(5), 3306-3317], which is based on an established auditory signal detection and masking model, are discussed. The key processing stages of these models for the prediction of speech intelligibility across a variety of acoustic conditions are addressed in relation to competing modeling approaches. The strengths and weaknesses of the modulation-based analysis are outlined and perspectives presented, particularly in connection with the challenge of predicting the consequences of individual hearing loss on speech intelligibility.