Towards a simplified and generalized monaural and binaural auditory model for psychoacoustics and speech intelligibility

Abstract

Auditory perception involves cues in the monaural auditory pathways, as well as binaural cues based on interaural differences. So far, auditory models have often focused on either monaural or binaural experiments in isolation. Although binaural models typically build upon stages of (existing) monaural models, only a few attempts have been made to extend a monaural model by a binaural stage using a unified decision stage for monaural and binaural cues. A typical prototype of binaural processing has been the classical equalization-cancelation mechanism, which either involves signal-adaptive delays and provides a single channel output, or can be implemented with tapped delays providing a high-dimensional multichannel output. This contribution extends the (monaural) generalized envelope power spectrum model by a non-adaptive binaural stage with only a few, fixed output channels. The binaural stage resembles features of physiologically motivated hemispheric binaural processing, as simplified signal-processing stages, yielding a 5-channel monaural and binaural matrix feature “decoder” (BMFD). The back end of the existing monaural model is applied to the BMFD output and calculates short-time envelope power and power features. The resulting model accounts for several published psychoacoustic and speech-intelligibility experiments and achieves a prediction performance comparable to existing state-of-the-art models with more complex binaural processing.

A model framework for simulating spatial hearing of bilateral cochlear implant users

“…Several studies have investigated the polarity sensitivity of auditory nerve fibers using eCAP recordings in human CI users [112,113], and to model such experiments, other AN models (e.g., [19,20,114]) can be incorporated. (3) Extensions to predict bilateral speech intelligibility are possible by connecting the AN spike outputs to the backend processing stages of other purposes such as an automatic speech recognition system (e.g., [37,110,111]) or by replacing it with more abstract internal model representations (e.g., [115,116]). ( 4) Applications for predicting CI users' bilateral loudness perception (e.g., [117]) by combining, e.g., the AN fiber outputs with a physiologically-motivated binaural loudness model (e.g., [118]).…”