A frequency-selective feedback model of auditory efferent suppression and its implications for the recognition of speech in noise

Abstract

The potential contribution of the peripheral auditory efferent system to our understanding of speech in a background of competing noise was studied using a computer model of the auditory periphery and assessed using an automatic speech recognition system. A previous study had shown that a fixed efferent attenuation applied to all channels of a multi-channel model could improve the recognition of connected digit triplets in noise [G. J. Brown, R. T. Ferry, and R. Meddis, J. Acoust. Soc. Am. 127, 943-954 (2010)]. In the current study an anatomically justified feedback loop was used to automatically regulate separate attenuation values for each auditory channel. This arrangement resulted in a further enhancement of speech recognition over fixed-attenuation conditions. Comparisons between multi-talker babble and pink noise interference conditions suggest that the benefit originates from the model's ability to modify the amount of suppression in each channel separately according to the spectral shape of the interfering sounds.

Effect of auditory efferent time-constant duration on speech recognition in noise

“…A similar improvement for speech recognition in pink noise was demonstrated by Clark et al (2012) using a variant of the same model in which the feedback signal dynamically controlled the amount of frequency-dependent attenuation; this is more representative of the physiological operation of the MOC (Guinan, 2006). The feedback (control) signal was dependent on the recent history of auditory nerve activity and was estimated from the temporally-smoothed firing rate using a first-order lowpass filter and a lag of 10 ms to account for the MOC-OHC synaptic minimum latency (Liberman, 1988).…”

“…In general, models incorporating efferent processing (in addition to afferent processing) using even a single long MOC time constant demonstrate a marked improvement in speech intelligibility in noise (Messing et al, 2009;Brown et al, 2010;Clark et al, 2012). Brown et al (2010) used an auditory model (as the "front-end" for an ASR system) with efferent-inspired feedback (Ferry and Meddis, 2007) operating as an openloop system with a fixed amount of efferent gain reduction across signal frequencies and found that speech reception thresholds in pink noise improved by about 10 dB a) Author to whom correspondence should be addressed.…”

Roles of the Contralateral Efferent Reflex in Hearing Demonstrated with Cochlear Implants

“…This idea is based on the fact that MOC efferent activation restores the dynamic range of auditory nerve fibre responses in noisy backgrounds to values observed in quiet (Fig. 5 in Guinan 2006), something that probably improves the neural coding of speech embedded in noise (Brown et al 2010;Chintanpalli et al 2012;Clark et al 2012). The evidence in support for this unmasking role of the MOCR during natural listening is, however, still indirect (Kim et al 2006).…”

Effect of Human Auditory Efferent Feedback on Cochlear Gain and Compression

“…Only a few studies have directly measured changes in BM response characteristics with efferent activation (Russell and Murugasu, 1997;e.g., Dolan et al, 1997), the results of which may be pertinent to the current study. Dolan et al (1997) studied changes in BM response with electrical stimulation of the OCB in guinea pigs and showed that the BM response function shifts to higher sound levels with efferent activation with a gain reduction of ϳ10 dB (Dolan et al, 1997) (Figs. 1, 2, and 3).…”