Effect of Reverberation on Neural Responses to Natural Speech in Rabbit Auditory Midbrain: No Evidence for a Neural Dereverberation Mechanism.

Reverberation is ubiquitous in everyday acoustic environments. It degrades both binaural cues and the envelope modulations of sounds and thus can impair speech perception. Still, both humans and animals can accurately perceive reverberant stimuli in most everyday settings. Previous neurophysiological and perceptual studies have suggested the existence of neural mechanisms that partially compensate for the effects of reverberation. However, these studies were limited by their use of either highly simplified stimuli or rudimentary reverberation simulations. To further characterize how reverberant stimuli are processed by the auditory system, we recorded single-unit (SU) and multiunit (MU) activity from the inferior colliculus (IC) of unanesthetized rabbits in response to natural speech utterances presented with no reverberation ("dry") and in various degrees of simulated reverberation (direct-to-reverberant energy ratios (DRRs) ranging from 9.4 to -8.2 dB). Linear stimulus reconstruction techniques (Mesgarani et al., 2009) were used to quantify the amount of speech information available in the responses of neural ensembles. We found that high-quality spectrogram reconstructions could be obtained for dry speech and in moderate reverberation from ensembles of 25 units. However, spectrogram reconstruction quality deteriorated in severe reverberation for both MUs and SUs such that the neural degradation paralleled the degradation in the stimulus spectrogram. Furthermore, spectrograms reconstructed from responses to reverberant stimuli resembled spectrograms of reverberant speech better than spectrograms of dry speech. Overall, the results provide no evidence for a dereverberation mechanism in neural responses from the rabbit IC when studied with linear reconstruction techniques.

A New Approach to Model Pitch Perception Using Sparse Coding.

Our acoustical environment abounds with repetitive sounds, some of which are related to pitch perception. It is still unknown how the auditory system, in processing these sounds, relates a physical stimulus and its percept. Since, in mammals, all auditory stimuli are conveyed into the nervous system through the auditory nerve (AN) fibers, a model should explain the perception of pitch as a function of this particular input. However, pitch perception is invariant to certain features of the physical stimulus. For example, a missing fundamental stimulus with resolved or unresolved harmonics, or a low and high-level amplitude stimulus with the same spectral content-these all give rise to the same percept of pitch. In contrast, the AN representations for these different stimuli are not invariant to these effects. In fact, due to saturation and non-linearity of both cochlear and inner hair cells responses, these differences are enhanced by the AN fibers. Thus there is a difficulty in explaining how pitch percept arises from the activity of the AN fibers. We introduce a novel approach for extracting pitch cues from the AN population activity for a given arbitrary stimulus. The method is based on a technique known as sparse coding (SC). It is the representation of pitch cues by a few spatiotemporal atoms (templates) from among a large set of possible ones (a dictionary). The amount of activity of each atom is represented by a non-zero coefficient, analogous to an active neuron. Such a technique has been successfully applied to other modalities, particularly vision. The model is composed of a cochlear model, an SC processing unit, and a harmonic sieve. We show that the model copes with different pitch phenomena: extracting resolved and non-resolved harmonics, missing fundamental pitches, stimuli with both high and low amplitudes, iterated rippled noises, and recorded musical instruments.